Impact of node deployment and routing for protection of critical infrastructures
- Subhan, Fazli, Noreen, Madiha, Imran, Muhammad, Tariq, Moeenuddin, Khan, Asfandyar, Shoaib, Muhammad
- Authors: Subhan, Fazli , Noreen, Madiha , Imran, Muhammad , Tariq, Moeenuddin , Khan, Asfandyar , Shoaib, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 11502-11514
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- Reviewed:
- Description: Recently, linear wireless sensor networks (LWSNs) have been eliciting increasing attention because of their suitability for applications such as the protection of critical infrastructures. Most of these applications require LWSN to remain operational for a longer period. However, the non-replenishable limited battery power of sensor nodes does not allow them to meet these expectations. Therefore, a shorter network lifetime is one of the most prominent barriers in large-scale deployment of LWSN. Unlike most existing studies, in this paper, we analyze the impact of node placement and clustering on LWSN network lifetime. First, we categorize and classify existing node placement and clustering schemes for LWSN and introduce various topologies for disparate applications. Then, we highlight the peculiarities of LWSN applications and discuss their unique characteristics. Several application domains of LWSN are described. We present three node placement strategies (i.e., linear sequential, linear parallel, and grid) and various deployment methods such as random, uniform, decreasing distance, and triangular. Extensive simulation experiments are conducted to analyze the performance of the three state-of-the-art routing protocols in the context of node deployment strategies and methods. The experimental results demonstrate that the node deployment strategies and methods significantly affect LWSN lifetime. © 2013 IEEE.
- Authors: Subhan, Fazli , Noreen, Madiha , Imran, Muhammad , Tariq, Moeenuddin , Khan, Asfandyar , Shoaib, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 11502-11514
- Full Text:
- Reviewed:
- Description: Recently, linear wireless sensor networks (LWSNs) have been eliciting increasing attention because of their suitability for applications such as the protection of critical infrastructures. Most of these applications require LWSN to remain operational for a longer period. However, the non-replenishable limited battery power of sensor nodes does not allow them to meet these expectations. Therefore, a shorter network lifetime is one of the most prominent barriers in large-scale deployment of LWSN. Unlike most existing studies, in this paper, we analyze the impact of node placement and clustering on LWSN network lifetime. First, we categorize and classify existing node placement and clustering schemes for LWSN and introduce various topologies for disparate applications. Then, we highlight the peculiarities of LWSN applications and discuss their unique characteristics. Several application domains of LWSN are described. We present three node placement strategies (i.e., linear sequential, linear parallel, and grid) and various deployment methods such as random, uniform, decreasing distance, and triangular. Extensive simulation experiments are conducted to analyze the performance of the three state-of-the-art routing protocols in the context of node deployment strategies and methods. The experimental results demonstrate that the node deployment strategies and methods significantly affect LWSN lifetime. © 2013 IEEE.
Pervasive blood pressure monitoring using Photoplethysmogram (PPG) sensor
- Riaz, Farhan, Azad, Muhammad, Arshad, Junaid, Imran, Muhammad, Hassan, Ali, Rehman, Saad
- Authors: Riaz, Farhan , Azad, Muhammad , Arshad, Junaid , Imran, Muhammad , Hassan, Ali , Rehman, Saad
- Date: 2019
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 98, no. (2019), p. 120-130
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- Description: Preventive healthcare requires continuous monitoring of the blood pressure (BP) of patients, which is not feasible using conventional methods. Photoplethysmogram (PPG) signals can be effectively used for this purpose as there is a physiological relation between the pulse width and BP and can be easily acquired using a wearable PPG sensor. However, developing real-time algorithms for wearable technology is a significant challenge due to various conflicting requirements such as high accuracy, computationally constrained devices, and limited power supply. In this paper, we propose a novel feature set for continuous, real-time identification of abnormal BP. This feature set is obtained by identifying the peaks and valleys in a PPG signal (using a peak detection algorithm), followed by the calculation of rising time, falling time and peak-to-peak distance. The histograms of these times are calculated to form a feature set that can be used for classification of PPG signals into one of the two classes: normal or abnormal BP. No public dataset is available for such study and therefore a prototype is developed to collect PPG signals alongside BP measurements. The proposed feature set shows very good performance with an overall accuracy of approximately 95%. Although the proposed feature set is effective, the significance of individual features varies greatly (validated using significance testing) which led us to perform weighted voting of features for classification by performing autoregressive modeling. Our experiments show that the simplest linear classifiers produce very good results indicating the strength of the proposed feature set. The weighted voting improves the results significantly, producing an overall accuracy of about 98%. Conclusively, the PPG signals can be effectively used to identify BP, and the proposed feature set is efficient and computationally feasible for implementation on standalone devices. © 2019 Elsevier B.V.
- Authors: Riaz, Farhan , Azad, Muhammad , Arshad, Junaid , Imran, Muhammad , Hassan, Ali , Rehman, Saad
- Date: 2019
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 98, no. (2019), p. 120-130
- Full Text:
- Reviewed:
- Description: Preventive healthcare requires continuous monitoring of the blood pressure (BP) of patients, which is not feasible using conventional methods. Photoplethysmogram (PPG) signals can be effectively used for this purpose as there is a physiological relation between the pulse width and BP and can be easily acquired using a wearable PPG sensor. However, developing real-time algorithms for wearable technology is a significant challenge due to various conflicting requirements such as high accuracy, computationally constrained devices, and limited power supply. In this paper, we propose a novel feature set for continuous, real-time identification of abnormal BP. This feature set is obtained by identifying the peaks and valleys in a PPG signal (using a peak detection algorithm), followed by the calculation of rising time, falling time and peak-to-peak distance. The histograms of these times are calculated to form a feature set that can be used for classification of PPG signals into one of the two classes: normal or abnormal BP. No public dataset is available for such study and therefore a prototype is developed to collect PPG signals alongside BP measurements. The proposed feature set shows very good performance with an overall accuracy of approximately 95%. Although the proposed feature set is effective, the significance of individual features varies greatly (validated using significance testing) which led us to perform weighted voting of features for classification by performing autoregressive modeling. Our experiments show that the simplest linear classifiers produce very good results indicating the strength of the proposed feature set. The weighted voting improves the results significantly, producing an overall accuracy of about 98%. Conclusively, the PPG signals can be effectively used to identify BP, and the proposed feature set is efficient and computationally feasible for implementation on standalone devices. © 2019 Elsevier B.V.
Protection of records and data authentication based on secret shares and watermarking
- Ali, Zulfiqar, Imran, Muhammad, McClean, Sally, Khan, Naveed, Shoaib, Muhammad
- Authors: Ali, Zulfiqar , Imran, Muhammad , McClean, Sally , Khan, Naveed , Shoaib, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 98, no. (2019), p. 331-341
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- Description: The rapid growth in communication technology facilitates the health industry in many aspects from transmission of sensor's data to real-time diagnosis using cloud-based frameworks. However, the secure transmission of data and its authenticity become a challenging task, especially, for health-related applications. The medical information must be accessible to only the relevant healthcare staff to avoid any unfortunate circumstances for the patient as well as for the healthcare providers. Therefore, a method to protect the identity of a patient and authentication of transmitted data is proposed in this study. The proposed method provides dual protection. First, it encrypts the identity using Shamir's secret sharing scheme without the increase in dimension of the original identity. Second, the identity is watermarked using zero-watermarking to avoid any distortion into the host signal. The experimental results show that the proposed method encrypts, embeds and extracts identities reliably. Moreover, in case of malicious attack, the method distorts the embedded identity which provides a clear indication of fabrication. An automatic disorder detection system using Mel-frequency cepstral coefficients and Gaussian mixture model is also implemented which concludes that malicious attacks greatly impact on the accurate diagnosis of disorders. © 2019 Elsevier B.V.
- Authors: Ali, Zulfiqar , Imran, Muhammad , McClean, Sally , Khan, Naveed , Shoaib, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 98, no. (2019), p. 331-341
- Full Text:
- Reviewed:
- Description: The rapid growth in communication technology facilitates the health industry in many aspects from transmission of sensor's data to real-time diagnosis using cloud-based frameworks. However, the secure transmission of data and its authenticity become a challenging task, especially, for health-related applications. The medical information must be accessible to only the relevant healthcare staff to avoid any unfortunate circumstances for the patient as well as for the healthcare providers. Therefore, a method to protect the identity of a patient and authentication of transmitted data is proposed in this study. The proposed method provides dual protection. First, it encrypts the identity using Shamir's secret sharing scheme without the increase in dimension of the original identity. Second, the identity is watermarked using zero-watermarking to avoid any distortion into the host signal. The experimental results show that the proposed method encrypts, embeds and extracts identities reliably. Moreover, in case of malicious attack, the method distorts the embedded identity which provides a clear indication of fabrication. An automatic disorder detection system using Mel-frequency cepstral coefficients and Gaussian mixture model is also implemented which concludes that malicious attacks greatly impact on the accurate diagnosis of disorders. © 2019 Elsevier B.V.
Real-time big data processing for anomaly detection : a survey
- Ariyaluran Habeeb, Riyaz, Nasaruddin, Fariza, Gani, Abdullah, Targio Hashem, Ibrahim, Ahmed, Ejaz, Imran, Muhammad
- Authors: Ariyaluran Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Targio Hashem, Ibrahim , Ahmed, Ejaz , Imran, Muhammad
- Date: 2019
- Type: Text , Journal article , Review
- Relation: International Journal of Information Management Vol. 45, no. (2019), p. 289-307
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- Description: The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed. © 2018 Elsevier Ltd
- Authors: Ariyaluran Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Targio Hashem, Ibrahim , Ahmed, Ejaz , Imran, Muhammad
- Date: 2019
- Type: Text , Journal article , Review
- Relation: International Journal of Information Management Vol. 45, no. (2019), p. 289-307
- Full Text:
- Reviewed:
- Description: The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed. © 2018 Elsevier Ltd
The role of big data analytics in industrial internet of things
- Rehman, Muhammad, Yaqoob, Ibrar, Salah, Khaled, Imran, Muhammad, Jayaraman, Prem, Perera, Charith
- Authors: Rehman, Muhammad , Yaqoob, Ibrar , Salah, Khaled , Imran, Muhammad , Jayaraman, Prem , Perera, Charith
- Date: 2019
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 99, no. (2019), p. 247-259
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- Description: Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due to limited computational, networking and storage resources at IoT device-end. Big data analytics (BDA) is expected to provide operational- and customer-level intelligence in IIoT systems. Although numerous studies on IIoT and BDA exist, only a few studies have explored the convergence of the two paradigms. In this study, we investigate the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems. We devise a taxonomy by classifying and categorising the literature on the basis of important parameters (e.g. data sources, analytics tools, analytics techniques, requirements, industrial analytics applications and analytics types). We present the frameworks and case studies of the various enterprises that have benefited from BDA. We also enumerate the considerable opportunities introduced by BDA in IIoT. We identify and discuss the indispensable challenges that remain to be addressed, serving as future research directions. © 2019 Elsevier B.V.
- Authors: Rehman, Muhammad , Yaqoob, Ibrar , Salah, Khaled , Imran, Muhammad , Jayaraman, Prem , Perera, Charith
- Date: 2019
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 99, no. (2019), p. 247-259
- Full Text:
- Reviewed:
- Description: Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due to limited computational, networking and storage resources at IoT device-end. Big data analytics (BDA) is expected to provide operational- and customer-level intelligence in IIoT systems. Although numerous studies on IIoT and BDA exist, only a few studies have explored the convergence of the two paradigms. In this study, we investigate the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems. We devise a taxonomy by classifying and categorising the literature on the basis of important parameters (e.g. data sources, analytics tools, analytics techniques, requirements, industrial analytics applications and analytics types). We present the frameworks and case studies of the various enterprises that have benefited from BDA. We also enumerate the considerable opportunities introduced by BDA in IIoT. We identify and discuss the indispensable challenges that remain to be addressed, serving as future research directions. © 2019 Elsevier B.V.
Ultra-reliable communications for industrial internet of things : design considerations and channel modeling
- Yang, Jingya, Ai, Bo, You, Ilsun, Imran, Muhammad, Wang, Longhe
- Authors: Yang, Jingya , Ai, Bo , You, Ilsun , Imran, Muhammad , Wang, Longhe
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Network Vol. 33, no. 4 (2019), p. 104-111
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- Description: Factory automation is the next industrial revolution. 5G and IIoT are enabling smart factories to seamlessly create a network of wirelessly connected machines and people that can instantaneously collect, analyze, and distribute real-time data. A 5G-enabled communication network for IIOT will boost overall efficiency, launching a new era of market opportunities and economic growth. This article presents the 5G-enabled system architecture and ultra-reliable use cases in smart factories associated with automated warehouses. In particular, for URLLC-based cases, key techniques and their corresponding solutions, including diversity for high reliability, short packets for low latency, and on-the-fly channel estimation and decoding for fast receiver processing, are discussed. Then the channel modeling requirements concerning technologies and systems are also identified in industrial scenarios. Ray tracing channel simulation can meet such requirements well, and based on that, the channel characteristic analysis is presented at 28 and 60 GHz for licensed and unlicensed band frequencies to exploit the available degrees of freedom in the channels. © 2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
- Authors: Yang, Jingya , Ai, Bo , You, Ilsun , Imran, Muhammad , Wang, Longhe
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Network Vol. 33, no. 4 (2019), p. 104-111
- Full Text:
- Reviewed:
- Description: Factory automation is the next industrial revolution. 5G and IIoT are enabling smart factories to seamlessly create a network of wirelessly connected machines and people that can instantaneously collect, analyze, and distribute real-time data. A 5G-enabled communication network for IIOT will boost overall efficiency, launching a new era of market opportunities and economic growth. This article presents the 5G-enabled system architecture and ultra-reliable use cases in smart factories associated with automated warehouses. In particular, for URLLC-based cases, key techniques and their corresponding solutions, including diversity for high reliability, short packets for low latency, and on-the-fly channel estimation and decoding for fast receiver processing, are discussed. Then the channel modeling requirements concerning technologies and systems are also identified in industrial scenarios. Ray tracing channel simulation can meet such requirements well, and based on that, the channel characteristic analysis is presented at 28 and 60 GHz for licensed and unlicensed band frequencies to exploit the available degrees of freedom in the channels. © 2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
A critical analysis of mobility management related issues of wireless sensor networks in cyber physical systems
- Al-Muhtadi, Jalal, Qiang, Ma, Zeb, Khan, Chaudhry, Junaid, Imran, Muhammad
- Authors: Al-Muhtadi, Jalal , Qiang, Ma , Zeb, Khan , Chaudhry, Junaid , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 16363-16376
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- Description: Mobility management has been a long-standing issue in mobile wireless sensor networks and especially in the context of cyber physical systems its implications are immense. This paper presents a critical analysis of the current approaches to mobility management by evaluating them against a set of criteria which are essentially inherent characteristics of such systems on which these approaches are expected to provide acceptable performance. We summarize these characteristics by using a quadruple set of metrics. Additionally, using this set we classify the various approaches to mobility management that are discussed in this paper. Finally, the paper concludes by reviewing the main findings and providing suggestions that will be helpful to guide future research efforts in the area. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
- Authors: Al-Muhtadi, Jalal , Qiang, Ma , Zeb, Khan , Chaudhry, Junaid , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 16363-16376
- Full Text:
- Reviewed:
- Description: Mobility management has been a long-standing issue in mobile wireless sensor networks and especially in the context of cyber physical systems its implications are immense. This paper presents a critical analysis of the current approaches to mobility management by evaluating them against a set of criteria which are essentially inherent characteristics of such systems on which these approaches are expected to provide acceptable performance. We summarize these characteristics by using a quadruple set of metrics. Additionally, using this set we classify the various approaches to mobility management that are discussed in this paper. Finally, the paper concludes by reviewing the main findings and providing suggestions that will be helpful to guide future research efforts in the area. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
A multivariant stream analysis approach to detect and mitigate DDoS attacks in vehicular ad hoc networks
- Kolandaisamy, Raenu, Md Noor, Rafidah, Ahmedy, Ismail, Ahmad, Iftikhar, Imran, Muhammad
- Authors: Kolandaisamy, Raenu , Md Noor, Rafidah , Ahmedy, Ismail , Ahmad, Iftikhar , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Wireless Communications and Mobile Computing Vol. 2018, no. (2018), p.
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- Description: Vehicular Ad Hoc Networks (VANETs) are rapidly gaining attention due to the diversity of services that they can potentially offer. However, VANET communication is vulnerable to numerous security threats such as Distributed Denial of Service (DDoS) attacks. Dealing with these attacks in VANET is a challenging problem. Most of the existing DDoS detection techniques suffer from poor accuracy and high computational overhead. To cope with these problems, we present a novel Multivariant Stream Analysis (MVSA) approach. The proposed MVSA approach maintains the multiple stages for detection DDoS attack in network. The Multivariant Stream Analysis gives unique result based on the Vehicle-to-Vehicle communication through Road Side Unit. The approach observes the traffic in different situations and time frames and maintains different rules for various traffic classes in various time windows. The performance of the MVSA is evaluated using an NS2 simulator. Simulation results demonstrate the effectiveness and efficiency of the MVSA regarding detection accuracy and reducing the impact on VANET communication. © 2018 Raenu Kolandaisamy et al. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
- Authors: Kolandaisamy, Raenu , Md Noor, Rafidah , Ahmedy, Ismail , Ahmad, Iftikhar , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Wireless Communications and Mobile Computing Vol. 2018, no. (2018), p.
- Full Text:
- Reviewed:
- Description: Vehicular Ad Hoc Networks (VANETs) are rapidly gaining attention due to the diversity of services that they can potentially offer. However, VANET communication is vulnerable to numerous security threats such as Distributed Denial of Service (DDoS) attacks. Dealing with these attacks in VANET is a challenging problem. Most of the existing DDoS detection techniques suffer from poor accuracy and high computational overhead. To cope with these problems, we present a novel Multivariant Stream Analysis (MVSA) approach. The proposed MVSA approach maintains the multiple stages for detection DDoS attack in network. The Multivariant Stream Analysis gives unique result based on the Vehicle-to-Vehicle communication through Road Side Unit. The approach observes the traffic in different situations and time frames and maintains different rules for various traffic classes in various time windows. The performance of the MVSA is evaluated using an NS2 simulator. Simulation results demonstrate the effectiveness and efficiency of the MVSA regarding detection accuracy and reducing the impact on VANET communication. © 2018 Raenu Kolandaisamy et al. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
A zero-watermarking algorithm for privacy protection in biomedical signals
- Ali, Zulfiqar, Imran, Muhammad, Alsulaiman, Mansour, Zia, Tanveer, Shoaib, Muhammad
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour , Zia, Tanveer , Shoaib, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 82, no. (2018), p. 290-303
- Full Text:
- Reviewed:
- Description: Confidentiality of health information is indispensable to protect privacy of an individual. However, recent advances in electronic healthcare systems allow transmission of sensitive information through the Internet, which is prone to various vulnerabilities, attacks and may leads to unauthorized disclosure. Such situations may not only create adverse effects for individuals but may also cause severe consequences such as hefty regulatory fines, bad publicity, legal fees, and forensics. To avoid such predicaments, a privacy protected healthcare system is proposed in this study that protects the identity of an individual as well as detects vocal fold disorders. The privacy of the developed healthcare system is based on the proposed zero-watermarking algorithm, which embeds a watermark in a secret key instead of the signals to avoid the distortion in an audio sample. The identity is protected by the generation of its secret shares through visual cryptography. The generated shares are embedded by finding the patterns into the audio with the application of one-dimensional local binary pattern. The proposed zero-watermarking algorithm is evaluated by using audio samples taken from the Massachusetts Eye and Ear Infirmary voice disorder database. Experimental results demonstrate that the proposed algorithm achieves imperceptibility and is reliable in its extraction of identity. In addition, the proposed algorithm does not affect the results of disorder detection and it is robust against noise attacks of various signal-to-noise ratios. © 2017 Elsevier B.V.
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour , Zia, Tanveer , Shoaib, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 82, no. (2018), p. 290-303
- Full Text:
- Reviewed:
- Description: Confidentiality of health information is indispensable to protect privacy of an individual. However, recent advances in electronic healthcare systems allow transmission of sensitive information through the Internet, which is prone to various vulnerabilities, attacks and may leads to unauthorized disclosure. Such situations may not only create adverse effects for individuals but may also cause severe consequences such as hefty regulatory fines, bad publicity, legal fees, and forensics. To avoid such predicaments, a privacy protected healthcare system is proposed in this study that protects the identity of an individual as well as detects vocal fold disorders. The privacy of the developed healthcare system is based on the proposed zero-watermarking algorithm, which embeds a watermark in a secret key instead of the signals to avoid the distortion in an audio sample. The identity is protected by the generation of its secret shares through visual cryptography. The generated shares are embedded by finding the patterns into the audio with the application of one-dimensional local binary pattern. The proposed zero-watermarking algorithm is evaluated by using audio samples taken from the Massachusetts Eye and Ear Infirmary voice disorder database. Experimental results demonstrate that the proposed algorithm achieves imperceptibility and is reliable in its extraction of identity. In addition, the proposed algorithm does not affect the results of disorder detection and it is robust against noise attacks of various signal-to-noise ratios. © 2017 Elsevier B.V.
Channel clustering and QoS level identification scheme for multi-channel cognitive radio networks
- Ali, Amjad, Yaqoob, Ibrar, Ahmed, Adnan, Imran, Muhammad, Kwak, Kyung
- Authors: Ali, Amjad , Yaqoob, Ibrar , Ahmed, Adnan , Imran, Muhammad , Kwak, Kyung
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 56, no. 4 (2018), p. 164-171
- Full Text:
- Reviewed:
- Description: The increasing popularity of wireless services and devices necessitates high bandwidth requirements; however, spectrum resources are not only limited but also heavily underutilized. Multiple license channels that support the same levels of QoS are desirable to resolve the problems posed by the scarcity and inefficient use of spectrum resources in multi-channel cognitive radio networks (MCRNs). One reason is that multimedia services and applications have distinct, stringent QoS requirements. However, due to a lack of coordination between primary and secondary users, identifying the QoS levels supported over available licensed channels has proven to be problematic and has yet to be attempted. This article presents a novel Bayesian non-parametric channel clustering scheme, which identifies the QoS levels supported over available license channels. The proposed scheme employs the infinite Gaussian mixture model and collapsed Gibbs sampler to identify the QoS levels from the feature space of the bit rate, packet delivery ratio, and packet delay variation of licensed channels. Moreover, the real measurements of wireless data traces and comparisons with baseline clustering schemes are used to evaluate the performance of the proposed scheme. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
- Authors: Ali, Amjad , Yaqoob, Ibrar , Ahmed, Adnan , Imran, Muhammad , Kwak, Kyung
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 56, no. 4 (2018), p. 164-171
- Full Text:
- Reviewed:
- Description: The increasing popularity of wireless services and devices necessitates high bandwidth requirements; however, spectrum resources are not only limited but also heavily underutilized. Multiple license channels that support the same levels of QoS are desirable to resolve the problems posed by the scarcity and inefficient use of spectrum resources in multi-channel cognitive radio networks (MCRNs). One reason is that multimedia services and applications have distinct, stringent QoS requirements. However, due to a lack of coordination between primary and secondary users, identifying the QoS levels supported over available licensed channels has proven to be problematic and has yet to be attempted. This article presents a novel Bayesian non-parametric channel clustering scheme, which identifies the QoS levels supported over available license channels. The proposed scheme employs the infinite Gaussian mixture model and collapsed Gibbs sampler to identify the QoS levels from the feature space of the bit rate, packet delivery ratio, and packet delay variation of licensed channels. Moreover, the real measurements of wireless data traces and comparisons with baseline clustering schemes are used to evaluate the performance of the proposed scheme. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
Chaos-based robust method of zero-watermarking for medical signals
- Ali, Zulfiqar, Imran, Muhammad, Alsulaiman, Mansour, Shoaib, Muhammad, Ullah, Sana
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour , Shoaib, Muhammad , Ullah, Sana
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 88, no. (2018), p. 400-412
- Full Text:
- Reviewed:
- Description: The growing use of wireless health data transmission via Internet of Things is significantly beneficial to the healthcare industry for optimal usage of health-related facilities. However, at the same time, the use raises concern of privacy protection. Health-related data are private and should be suitably protected. Several pathologies, such as vocal fold disorders, indicate high risks of prevalence in individuals with voice-related occupations, such as teachers, singers, and lawyers. Approximately, one-third of the world population suffers from the voice-related problems during the life span and unauthorized access to their data can create unavoidable circumstances in their personal and professional lives. In this study, a zero-watermarking method is proposed and implemented to protect the identity of patients who suffer from vocal fold disorders. In the proposed method, an image for a patient's identity is generated and inserted into secret keys instead of a host medical signal. Consequently, imperceptibility is naturally achieved. The locations for the insertion of the watermark are determined by a computation of local binary patterns from the time–frequency spectrum. The spectrum is calculated for low frequencies such that it may not be affected by noise attacks. The experimental results suggest that the proposed method has good performance and robustness against noise, and it is reliable in the recovery of an individual's identity. © 2018 Elsevier B.V.
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour , Shoaib, Muhammad , Ullah, Sana
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 88, no. (2018), p. 400-412
- Full Text:
- Reviewed:
- Description: The growing use of wireless health data transmission via Internet of Things is significantly beneficial to the healthcare industry for optimal usage of health-related facilities. However, at the same time, the use raises concern of privacy protection. Health-related data are private and should be suitably protected. Several pathologies, such as vocal fold disorders, indicate high risks of prevalence in individuals with voice-related occupations, such as teachers, singers, and lawyers. Approximately, one-third of the world population suffers from the voice-related problems during the life span and unauthorized access to their data can create unavoidable circumstances in their personal and professional lives. In this study, a zero-watermarking method is proposed and implemented to protect the identity of patients who suffer from vocal fold disorders. In the proposed method, an image for a patient's identity is generated and inserted into secret keys instead of a host medical signal. Consequently, imperceptibility is naturally achieved. The locations for the insertion of the watermark are determined by a computation of local binary patterns from the time–frequency spectrum. The spectrum is calculated for low frequencies such that it may not be affected by noise attacks. The experimental results suggest that the proposed method has good performance and robustness against noise, and it is reliable in the recovery of an individual's identity. © 2018 Elsevier B.V.
Co-EEORS : cooperative energy efficient optimal relay selection protocol for underwater wireless sensor networks
- Khan, Anwar, Ali, Ihsan, Rahman, Atiq, Imran, Muhammad, Amin, Fazal, Mahmood, Hasan
- Authors: Khan, Anwar , Ali, Ihsan , Rahman, Atiq , Imran, Muhammad , Amin, Fazal , Mahmood, Hasan
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 28777-28789
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- Description: Cooperative routing mitigates the adverse channel effects in the harsh underwater environment and ensures reliable delivery of packets from the bottom to the surface of water. Cooperative routing is analogous to sparse recovery in that faded copies of data packets are processed by the destination node to extract the desired information. However, it usually requires information about the two or three position coordinates of the nodes. It also requires the synchronization of the source, relay, and destination nodes. These features make the cooperative routing a challenging task as sensor nodes move with water currents. Moreover, the data packets are simply discarded if the acceptable threshold is not met at the destination. This threatens the reliable delivery of data to the final destination. To cope with these challenges, this paper proposes a cooperative energy-efficient optimal relay selection protocol for underwater wireless sensor networks. Unlike the existing routing protocols involving cooperation, the proposed scheme combines location and depth of the sensor nodes to select the destination nodes. Combination of these two parameters does not involve knowing the position coordinates of the nodes and results in selection of the destination nodes closest to the water surface. As a result, data packets are less affected by the channel properties. In addition, a source node chooses a relay node and a destination node. Data packets are sent to the destination node by the relay node as soon as the relay node receives them. This eliminates the need for synchronization among the source, relay, and destination nodes. Moreover, the destination node acknowledges the source node about the successful reception or retransmission of the data packets. This overcomes the packets drop. Based on simulation results, the proposed scheme is superior in delivering packets to the final destination than some existing techniques. © 2013 IEEE.
- Authors: Khan, Anwar , Ali, Ihsan , Rahman, Atiq , Imran, Muhammad , Amin, Fazal , Mahmood, Hasan
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 28777-28789
- Full Text:
- Reviewed:
- Description: Cooperative routing mitigates the adverse channel effects in the harsh underwater environment and ensures reliable delivery of packets from the bottom to the surface of water. Cooperative routing is analogous to sparse recovery in that faded copies of data packets are processed by the destination node to extract the desired information. However, it usually requires information about the two or three position coordinates of the nodes. It also requires the synchronization of the source, relay, and destination nodes. These features make the cooperative routing a challenging task as sensor nodes move with water currents. Moreover, the data packets are simply discarded if the acceptable threshold is not met at the destination. This threatens the reliable delivery of data to the final destination. To cope with these challenges, this paper proposes a cooperative energy-efficient optimal relay selection protocol for underwater wireless sensor networks. Unlike the existing routing protocols involving cooperation, the proposed scheme combines location and depth of the sensor nodes to select the destination nodes. Combination of these two parameters does not involve knowing the position coordinates of the nodes and results in selection of the destination nodes closest to the water surface. As a result, data packets are less affected by the channel properties. In addition, a source node chooses a relay node and a destination node. Data packets are sent to the destination node by the relay node as soon as the relay node receives them. This eliminates the need for synchronization among the source, relay, and destination nodes. Moreover, the destination node acknowledges the source node about the successful reception or retransmission of the data packets. This overcomes the packets drop. Based on simulation results, the proposed scheme is superior in delivering packets to the final destination than some existing techniques. © 2013 IEEE.
Extending the technology acceptance model for use of e-learning systems by digital learners
- Hanif, Aamer, Jamal, Faheem, Imran, Muhammad
- Authors: Hanif, Aamer , Jamal, Faheem , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 73395-73404
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- Description: Technology-based learning systems enable enhanced student learning in higher-education institutions. This paper evaluates the factors affecting behavioral intention of students toward using e-learning systems in universities to augment classroom learning. Based on the technology acceptance model, this paper proposes six external factors that influence the behavioral intention of students toward use of e-learning. A quantitative approach involving structural equation modeling is adopted, and research data collected from 437 undergraduate students enrolled in three academic programs is used for analysis. Results indicate that subjective norm, perception of external control, system accessibility, enjoyment, and result demonstrability have a significant positive influence on perceived usefulness and on perceived ease of use of the e-learning system. This paper also examines the relevance of some previously used external variables, e.g., self-efficacy, experience, and computer anxiety, for present-world students who have been brought up as digital learners and have higher levels of computer literacy and experience. © 2018 IEEE.
- Authors: Hanif, Aamer , Jamal, Faheem , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 73395-73404
- Full Text:
- Reviewed:
- Description: Technology-based learning systems enable enhanced student learning in higher-education institutions. This paper evaluates the factors affecting behavioral intention of students toward using e-learning systems in universities to augment classroom learning. Based on the technology acceptance model, this paper proposes six external factors that influence the behavioral intention of students toward use of e-learning. A quantitative approach involving structural equation modeling is adopted, and research data collected from 437 undergraduate students enrolled in three academic programs is used for analysis. Results indicate that subjective norm, perception of external control, system accessibility, enjoyment, and result demonstrability have a significant positive influence on perceived usefulness and on perceived ease of use of the e-learning system. This paper also examines the relevance of some previously used external variables, e.g., self-efficacy, experience, and computer anxiety, for present-world students who have been brought up as digital learners and have higher levels of computer literacy and experience. © 2018 IEEE.
Performance analysis of priority-based IEEE 802.15.6 protocol in saturated traffic conditions
- Ullah, Sana, Tovar, Eduardo, Kim, Ki, Kim, Kyong, Imran, Muhammad
- Authors: Ullah, Sana , Tovar, Eduardo , Kim, Ki , Kim, Kyong , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 66198-66209
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- Description: Recent advancement in internet of medical things has enabled deployment of miniaturized, intelligent, and low-power medical devices in, on, or around a human body for unobtrusive and remote health monitoring. The IEEE 802.15.6 standard facilitates such monitoring by enabling low-power and reliable wireless communication between the medical devices. The IEEE 802.15.6 standard employs a carrier sense multiple access with collision avoidance protocol for resource allocation. It utilizes a priority-based backoff procedure by adjusting the contention window bounds of devices according to user requirements. As the performance of this protocol is considerably affected when the number of devices increases, we propose an accurate analytical model to estimate the saturation throughput, mean energy consumption, and mean delay over the number of devices. We assume an error-prone channel with saturated traffic conditions. We determine the optimal performance bounds for a fixed number of devices in different priority classes with different values of bit error ratio. We conclude that high-priority devices obtain quick and reliable access to the error-prone channel compared to low-priority devices. The proposed model is validated through extensive simulations. The performance bounds obtained in our analysis can be used to understand the tradeoffs between different priority levels and network performance. © 2018 IEEE.
- Authors: Ullah, Sana , Tovar, Eduardo , Kim, Ki , Kim, Kyong , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 66198-66209
- Full Text:
- Reviewed:
- Description: Recent advancement in internet of medical things has enabled deployment of miniaturized, intelligent, and low-power medical devices in, on, or around a human body for unobtrusive and remote health monitoring. The IEEE 802.15.6 standard facilitates such monitoring by enabling low-power and reliable wireless communication between the medical devices. The IEEE 802.15.6 standard employs a carrier sense multiple access with collision avoidance protocol for resource allocation. It utilizes a priority-based backoff procedure by adjusting the contention window bounds of devices according to user requirements. As the performance of this protocol is considerably affected when the number of devices increases, we propose an accurate analytical model to estimate the saturation throughput, mean energy consumption, and mean delay over the number of devices. We assume an error-prone channel with saturated traffic conditions. We determine the optimal performance bounds for a fixed number of devices in different priority classes with different values of bit error ratio. We conclude that high-priority devices obtain quick and reliable access to the error-prone channel compared to low-priority devices. The proposed model is validated through extensive simulations. The performance bounds obtained in our analysis can be used to understand the tradeoffs between different priority levels and network performance. © 2018 IEEE.
Technology-assisted decision support system for efficient water utilization : a real-time testbed for irrigation using wireless sensor networks
- Khan, Rahim, Ali, Ihsan, Zakarya, Muhammad, Ahmad, Mushtaq, Imran, Muhammad, Shoaib, Muhammad
- Authors: Khan, Rahim , Ali, Ihsan , Zakarya, Muhammad , Ahmad, Mushtaq , Imran, Muhammad , Shoaib, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 25686-25697
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- Description: Scientific organizations and researchers are eager to apply recent technological advancements, such as sensors and actuators, in different application areas, including environmental monitoring, creation of intelligent buildings, and precision agriculture. Technology-assisted irrigation for agriculture is a major research innovation which eases the work of farmers and prevents water wastage. Wireless sensor networks (WSNs) are used as sensor nodes that directly interact with the physical environment and provide real-time data that are useful in identifying regions in need, particularly in agricultural fields. This paper presents an efficient methodology that employs WSN as a data collection tool and a decision support system (DSS). The proposed DSS can assist farmers in their manual irrigation procedures or automate irrigation activities. Water-deficient sites in both scenarios are identified by using soil moisture and environmental data sensors. However, the proposed system's accuracy is directly proportional to the accuracy of dynamic data generated by the deployed WSN. A simplified outlier-detection algorithm is thus presented and integrated with the proposed DSS to fine-tune the collected data prior to processing. The complexity of the algorithm is O(1) for dynamic datasets generated by sensor nodes and O(n) for static datasets. Different issues in technology-assisted irrigation management and their solutions are also addressed. © 2013 IEEE.
- Authors: Khan, Rahim , Ali, Ihsan , Zakarya, Muhammad , Ahmad, Mushtaq , Imran, Muhammad , Shoaib, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 25686-25697
- Full Text:
- Reviewed:
- Description: Scientific organizations and researchers are eager to apply recent technological advancements, such as sensors and actuators, in different application areas, including environmental monitoring, creation of intelligent buildings, and precision agriculture. Technology-assisted irrigation for agriculture is a major research innovation which eases the work of farmers and prevents water wastage. Wireless sensor networks (WSNs) are used as sensor nodes that directly interact with the physical environment and provide real-time data that are useful in identifying regions in need, particularly in agricultural fields. This paper presents an efficient methodology that employs WSN as a data collection tool and a decision support system (DSS). The proposed DSS can assist farmers in their manual irrigation procedures or automate irrigation activities. Water-deficient sites in both scenarios are identified by using soil moisture and environmental data sensors. However, the proposed system's accuracy is directly proportional to the accuracy of dynamic data generated by the deployed WSN. A simplified outlier-detection algorithm is thus presented and integrated with the proposed DSS to fine-tune the collected data prior to processing. The complexity of the algorithm is O(1) for dynamic datasets generated by sensor nodes and O(n) for static datasets. Different issues in technology-assisted irrigation management and their solutions are also addressed. © 2013 IEEE.
A quantitative risk assessment model involving frequency and threat degree under line-of-business services for infrastructure of emerging sensor networks
- Jing, Xu, Hu, Hanwen, Yang, Huijun, Au, Man, Li, Shuqin, Xiong, Naixue, Imran, Muhammad, Vasilakos, Athanasios
- Authors: Jing, Xu , Hu, Hanwen , Yang, Huijun , Au, Man , Li, Shuqin , Xiong, Naixue , Imran, Muhammad , Vasilakos, Athanasios
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 3 (2017), p.
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- Description: The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider’s server contains a lot of valuable resources. LoBSs’ users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs’ risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs’ risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Jing, Xu , Hu, Hanwen , Yang, Huijun , Au, Man , Li, Shuqin , Xiong, Naixue , Imran, Muhammad , Vasilakos, Athanasios
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 3 (2017), p.
- Full Text:
- Reviewed:
- Description: The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider’s server contains a lot of valuable resources. LoBSs’ users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs’ risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs’ risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
An automatic digital audio authentication/forensics system
- Ali, Zulfiqar, Imran, Muhammad, Alsulaiman, Mansour
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 2994-3007
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- Description: With the continuous rise in ingenious forgery, a wide range of digital audio authentication applications are emerging as a preventive and detective control in real-world circumstances, such as forged evidence, breach of copyright protection, and unauthorized data access. To investigate and verify, this paper presents a novel automatic authentication system that differentiates between the forged and original audio. The design philosophy of the proposed system is primarily based on three psychoacoustic principles of hearing, which are implemented to simulate the human sound perception system. Moreover, the proposed system is able to classify between the audio of different environments recorded with the same microphone. To authenticate the audio and environment classification, the computed features based on the psychoacoustic principles of hearing are dangled to the Gaussian mixture model to make automatic decisions. It is worth mentioning that the proposed system authenticates an unknown speaker irrespective of the audio content i.e., independent of narrator and text. To evaluate the performance of the proposed system, audios in multi-environments are forged in such a way that a human cannot recognize them. Subjective evaluation by three human evaluators is performed to verify the quality of the generated forged audio. The proposed system provides a classification accuracy of 99.2% ± 2.6. Furthermore, the obtained accuracy for the other scenarios, such as text-dependent and text-independent audio authentication, is 100% by using the proposed system. © 2017 IEEE.
- Authors: Ali, Zulfiqar , Imran, Muhammad , Alsulaiman, Mansour
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 2994-3007
- Full Text:
- Reviewed:
- Description: With the continuous rise in ingenious forgery, a wide range of digital audio authentication applications are emerging as a preventive and detective control in real-world circumstances, such as forged evidence, breach of copyright protection, and unauthorized data access. To investigate and verify, this paper presents a novel automatic authentication system that differentiates between the forged and original audio. The design philosophy of the proposed system is primarily based on three psychoacoustic principles of hearing, which are implemented to simulate the human sound perception system. Moreover, the proposed system is able to classify between the audio of different environments recorded with the same microphone. To authenticate the audio and environment classification, the computed features based on the psychoacoustic principles of hearing are dangled to the Gaussian mixture model to make automatic decisions. It is worth mentioning that the proposed system authenticates an unknown speaker irrespective of the audio content i.e., independent of narrator and text. To evaluate the performance of the proposed system, audios in multi-environments are forged in such a way that a human cannot recognize them. Subjective evaluation by three human evaluators is performed to verify the quality of the generated forged audio. The proposed system provides a classification accuracy of 99.2% ± 2.6. Furthermore, the obtained accuracy for the other scenarios, such as text-dependent and text-independent audio authentication, is 100% by using the proposed system. © 2017 IEEE.
Blind detection of copy-move forgery in digital audio forensics
- Imran, Muhammad, Ali, Zulfiqar, Bakhsh, Sheikh, Akram, Sheeraz
- Authors: Imran, Muhammad , Ali, Zulfiqar , Bakhsh, Sheikh , Akram, Sheeraz
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 12843-12855
- Full Text:
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- Description: Although copy-move forgery is one of the most common fabrication techniques, blind detection of such tampering in digital audio is mostly unexplored. Unlike active techniques, blind forgery detection is challenging, because it does not embed a watermark or signature in an audio that is unknown in most of the real-life scenarios. Therefore, forgery localization becomes more challenging, especially when using blind methods. In this paper, we propose a novel method for blind detection and localization of copy-move forgery. One of the most crucial steps in the proposed method is a voice activity detection (VAD) module for investigating audio recordings to detect and localize the forgery. The VAD module is equally vital for the development of the copy-move forgery database, wherein audio samples are generated by using the recordings of various types of microphones. We employ a chaotic theory to copy and move the text in generated forged recordings to ensure forgery localization at any place in a recording. The VAD module is responsible for the extraction of words in a forged audio, these words are analyzed by applying a 1-D local binary pattern operator. This operator provides the patterns of extracted words in the form of histograms. The forged parts (copy and move text) have similar histograms. An accuracy of 96.59% is achieved, the proposed method is deemed robust against noise. © 2013 IEEE.
- Authors: Imran, Muhammad , Ali, Zulfiqar , Bakhsh, Sheikh , Akram, Sheeraz
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 12843-12855
- Full Text:
- Reviewed:
- Description: Although copy-move forgery is one of the most common fabrication techniques, blind detection of such tampering in digital audio is mostly unexplored. Unlike active techniques, blind forgery detection is challenging, because it does not embed a watermark or signature in an audio that is unknown in most of the real-life scenarios. Therefore, forgery localization becomes more challenging, especially when using blind methods. In this paper, we propose a novel method for blind detection and localization of copy-move forgery. One of the most crucial steps in the proposed method is a voice activity detection (VAD) module for investigating audio recordings to detect and localize the forgery. The VAD module is equally vital for the development of the copy-move forgery database, wherein audio samples are generated by using the recordings of various types of microphones. We employ a chaotic theory to copy and move the text in generated forged recordings to ensure forgery localization at any place in a recording. The VAD module is responsible for the extraction of words in a forged audio, these words are analyzed by applying a 1-D local binary pattern operator. This operator provides the patterns of extracted words in the form of histograms. The forged parts (copy and move text) have similar histograms. An accuracy of 96.59% is achieved, the proposed method is deemed robust against noise. © 2013 IEEE.
Characterizing the role of vehicular cloud computing in road traffic management
- Ahmad, Iftikhar, Noor, Rafidah, Ali, Ihsan, Imran, Muhammad, Vasilakos, Athanasios
- Authors: Ahmad, Iftikhar , Noor, Rafidah , Ali, Ihsan , Imran, Muhammad , Vasilakos, Athanasios
- Date: 2017
- Type: Text , Journal article
- Relation: International Journal of Distributed Sensor Networks Vol. 13, no. 5 (2017), p.
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- Description: Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles. © The Author(s) 2017.
- Authors: Ahmad, Iftikhar , Noor, Rafidah , Ali, Ihsan , Imran, Muhammad , Vasilakos, Athanasios
- Date: 2017
- Type: Text , Journal article
- Relation: International Journal of Distributed Sensor Networks Vol. 13, no. 5 (2017), p.
- Full Text:
- Reviewed:
- Description: Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles. © The Author(s) 2017.
Design and analysis of an efficient energy algorithm in wireless social sensor networks
- Xiong, Naixue, Zhang, Longzhen, Zhang, Wei, Vasilakos, Athanasios, Imran, Muhammad
- Authors: Xiong, Naixue , Zhang, Longzhen , Zhang, Wei , Vasilakos, Athanasios , Imran, Muhammad
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 10 (2017), p.
- Full Text:
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- Description: Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Xiong, Naixue , Zhang, Longzhen , Zhang, Wei , Vasilakos, Athanasios , Imran, Muhammad
- Date: 2017
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 17, no. 10 (2017), p.
- Full Text:
- Reviewed:
- Description: Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.