List of Titles

Machine learning for 5G security : architecture, recent advances, and challenges

- Afaq, Amir, Haider, Noman, Baig, Muhammad, Khan, Komal, Imran, Muhammad, Razzak, Imran

Authors: Afaq, Amir , Haider, Noman , Baig, Muhammad , Khan, Komal , Imran, Muhammad , Razzak, Imran
Date: 2021
Type: Text , Journal article
Relation: Ad Hoc Networks Vol. 123, no. (2021), p.
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Description: The granularization of crucial network functions implementation using software-centric, and virtualized approaches in 5G networks have brought forth unprecedented security challenges in general and privacy concerns. Moreover, these software components’ premature deployment and compromised supply chain put the individual network components at risk and have a ripple effect for the rest of the network. Some of the novel threats to 5G assets include tampering in identity and access management, supply-chain poisoning, masquerade and bot attacks, loop-holes in source codes. Machine learning (ML) in this context can help to provide heavily dynamic and robust security mechanisms for the software-centric architecture of 5G Networks. ML models’ development and implementation also rely on programmable environments; hence, they can play a vital role in designing, modelling, and automating efficient security protocols. This article presents the threat landscape across 5G networks and discusses the feasibility and architecture of different ML-based models to counter these threats. Also, we present the architecture for automated threat intelligence using cooperative and coordinated ML to secure 5G assets and infrastructure. We also present the summary of closely related existing works along with future research challenges. © 2021 Elsevier B.V.

Cognitive sensors based on ridge phase-smoothing localization and multiregional histograms of oriented gradients

- Chen, Bo-Wei, Rho, Seungmin, Imran, Muhammad, Guizani, Mohsen, Fan, Wei-Kang

Authors: Chen, Bo-Wei , Rho, Seungmin , Imran, Muhammad , Guizani, Mohsen , Fan, Wei-Kang
Date: 2019
Type: Text , Journal article
Relation: IEEE Transactions on Emerging Topics in Computing Vol. 7, no. 1 (2019), p. 123-134
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Description: This study presents a smart cognitive sensor 'iRecorder' that can spontaneously locate speakers among attendees at a boardroom using ubiquitous arrays of audiovisual sensors. The proposed system 'iRecorder' consists of two major components - Sound localization and mouth tracking. For acoustic processing, this work proposes ridge phase-smoothing direction-of-arrival (DOA) estimation, which refines the distorted phase of a signal and robustly determines acoustic directions. During visual detection, this study develops novel Multiregional Histograms of Oriented Gradients (MHOGs) to model an uttering mouth. Unlike HOGs, the proposed feature is no longer limited to fixed-sized windows or blocks. It relies on facial regions. Finally, the system uses a fusion mechanism that integrates both clues from audiovisual sensors based on majority voting to target an actual speaker. The experimental result of DOA estimation showed that the directional errors were successfully improved by 6.6 degree on average. Concerning detection of talking faces, the accuracy reached as high as a rate of 85.19 percent. The fusion test results also supported the effectiveness of the system. Such findings reveal that the proposed system is superior to the other approaches and establishes its feasibility. © 2013 IEEE.

Process state synchronization-based application execution management for mobile edge/cloud computing

- Ahmed, Ejaz, Naveed, Anjum, Gani, Abdullah, Hamid, Siti, Imran, Muhammad, Guizani, Mohsen

Authors: Ahmed, Ejaz , Naveed, Anjum , Gani, Abdullah , Hamid, Siti , Imran, Muhammad , Guizani, Mohsen
Date: 2019
Type: Text , Journal article
Relation: Future Generation Computer Systems Vol. 91, no. (2019), p. 579-589
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Description: Mobile cloud computing (MCC) and mobile edge computing (MEC) facilitate the mobile devices to augment their capabilities by utilizing the resources and services offered by Cloud and Edge Cloud, respectively. However, due to mobility, network connection becomes unstable that causes application execution disruption. Such disruption increases the execution time and in some cases restrain the mobile devices from getting execution results from the cloud. This research work analyzes the impact of user mobility on the execution of cloud-based mobile applications. We propose a Process State Synchronization (PSS)-based execution management to solve the aforementioned problem. We analytically compute a sufficient condition on synchronization interval that ensure reduction in mobile application execution time under PSS in case of disconnection. Similarly, we compute the upper bound on synchronization interval whereby a larger synchronization interval did not result in significant benefits in terms of execution time for the mobile application. The analytical results were confirmed by the sample implementation of PSS with the computed synchronization intervals. Moreover, we also compare the performance of proposed solution with the state-of-the-art solutions. The results show that the PSS-based execution outperforms the other contemporary solutions. © 2018 Elsevier B.V.

Congestion avoidance through fog computing in internet of vehicles

- Yaqoob, Shumayla, Ullah, Ata, Akbar, Muhammad, Imran, Muhammad, Shoaib, Muhammad

Authors: Yaqoob, Shumayla , Ullah, Ata , Akbar, Muhammad , Imran, Muhammad , Shoaib, Muhammad
Date: 2019
Type: Text , Journal article
Relation: Journal of Ambient Intelligence and Humanized Computing Vol. 10, no. 10 (2019), p. 3863-3877
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Description: Recently, internet of vehicles (IoVs) is captivating a lot of interest due to a wide range of applications in various domains. These applications rely on up-to-date information of vehicles for provisioning various services. However, frequent message transmissions by a sheer number of vehicles may not only engulf a centralized server but may also cause a severe congestion which is not suitable for ongoing services specially in emergency situations. The aim of this study is to reduce congestion and messaging overhead. This paper presents a fog-assisted congestion avoidance scheme for IoV named energy efficient message dissemination (E2MD). Unlike most of the existing schemes, E2MD capitalizes the merits of fog computing to minimize communication cost and manage services. Each vehicle is required to update their status to a fog server frequently, either directly or through intermediate nodes. In case of an emergency, the fog server will timely inform upcoming traffic to slow down, dispatch rescue teams to provide necessary services, and coordinate patrolling missions to clear the road. Moreover, failure detection and recovery mechanisms are also presented to ensure availability of the fog server. The performance of the proposed scheme is validated through NS 2.35 simulations. Simulation results confirm the performance reign of E2MD compared to contemporary schemes in terms of latency and communication cost. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

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Implicit feedback-based group recommender system for internet of things applications

- Guo, Zhiwei, Yu, Keping, Guo, Tan, Bashir, Ali, Imran, Muhammad, Guizani, Mohsen

Authors: Guo, Zhiwei , Yu, Keping , Guo, Tan , Bashir, Ali , Imran, Muhammad , Guizani, Mohsen
Date: 2020
Type: Text , Conference paper
Relation: 2020 IEEE Global Communications Conference, GLOBECOM 2020, Virtual Taipei, 7-11 December 2020 Vol. 2020-January
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Description: With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedbacks. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game (GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods. © 2020 IEEE.

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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.

Cloud-based smart manufacturing for personalized candy packing application

- Wang, Shiyong, Wan, Jiafu, Imran, Muhammad, Li, Di, Zhang, Chunhua

Authors: Wang, Shiyong , Wan, Jiafu , Imran, Muhammad , Li, Di , Zhang, Chunhua
Date: 2018
Type: Text , Journal article
Relation: Journal of Supercomputing Vol. 74, no. 9 (2018), p. 4339-4357
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Description: Industry 4.0 has been proposed to address personalized consumption demands by building cyber-physical production systems for smart manufacturing. Although cloud manufacturing and some integrated frameworks for smart factory have been presented in literatures, it still lacks industrial applications. In this paper, we use personalized candy packing application as a demonstration to illustrate our smart factory design. We first describe the component layers of the smart factory, i.e., physical devices, private cloud, client terminals, and network, to enable the smart factory to be integrated with other systems, such as banks and logistical network, to cope with personalized consumption demands. Then, we present a scheme for inter-layered interaction. As for the physical devices, we also design an intra-layered negotiation mechanism to implement dynamic reconfiguration, so that the system can support hybrid production of multi-typed products. Finally, we give experimental results to verify efficiency, self-organized process, and hybrid production paradigm of the proposed system. © 2016, Springer Science+Business Media New York.

5G for Vehicular Communications

- Shah, Syed, Ahmed, Ejaz, Imran, Muhammad, Zeadally, Sherali

Authors: Shah, Syed , Ahmed, Ejaz , Imran, Muhammad , Zeadally, Sherali
Date: 2018
Type: Text , Journal article
Relation: IEEE Communications Magazine Vol. 56, no. 1 (2018), p. 111-117
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Description: 5G is ongoing, and it is an emerging platform that not only aims to augment existing but also introduce a plethora of novel applications that require ultra-reliable low-latency communication. It is a new radio access technology that provides building blocks to retrofit existing platforms (e.g., 2G, 3G, 4G, and WiFi) for greater coverage, accessibility, and higher network density with respect to cells and devices. It implies that 5G aims to satisfy a diverse set of communication requirements of the various stakeholders. Among the stakeholders, vehicles, in particular, will benefit from 5G at both the system and application levels. The authors present a tutorial perspective on vehicular communications using the building blocks provided by 5G. First, we identify and describe key requirements of emerging vehicular communications and assess existing standards to determine their limitations. Then we provide a glimpse of the adopted 5G architecture and identify some of its promising salient features for vehicular communications. Finally, key 5G building blocks (i.e., proximity services, mobile edge computing and network slicing) are explored in the context of vehicular communications, and associated design challenges are highlighted. © 1979-2012 IEEE.

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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.

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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**

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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.

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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.

A hybrid precoding- and filtering-based uplink MC-LNOMA scheme for 5G cellular networks with reduced PAPR

- Baig, Imran, Farooq, Umer, Ahmed, Ejaz, Imran, Muhammad, Shoaib, Muhammad

Authors: Baig, Imran , Farooq, Umer , Ahmed, Ejaz , Imran, Muhammad , Shoaib, Muhammad
Date: 2018
Type: Text , Journal article
Relation: Transactions on Emerging Telecommunications Technologies Vol. 29, no. 10 (2018), p.
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Description: Uplink multicarrier localized nonorthogonal multiple access (MC-LNOMA) is a variant of hybrid nonorthogonal multiple access, where subcarrier mapping is performed in localized mode. MC-LNOMA is one of the most prominent emerging schemes and likely to be employed in the forthcoming fifth-generation cellular networks due to its massive connectivity, spectral efficiency, better cell coverage capability, and higher data rate. It may employ orthogonal frequency-division multiple access due to the technical ripeness. However, schemes based on orthogonal frequency-division multiple access all suffer from the high peak-to-average power ratio problem. Therefore, in this paper, a new finite impulse response filter–based discrete cosine transform–precoded uplink MC-LNOMA scheme is presented for peak-to-average power ratio reduction. MATLAB simulations demonstrate the performance supremacy of the proposed scheme compared to contemporary schemes such as discrete cosine transform–precoded uplink MC-LNOMA and nonprecoded uplink MC-LNOMA. © 2018 John Wiley & Sons, Ltd.

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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
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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.

Recent advances and challenges in mobile big data

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Shuja, Junaid, Imran, Muhammad

Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Shuja, Junaid , Imran, Muhammad
Date: 2018
Type: Text , Journal article
Relation: IEEE Communications Magazine Vol. 56, no. 2 (2018), p. 102-108
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Description: The unabated flurry of research activities dedicated to gaining business insights from a flood of data generated by heterogeneous mobile sources, such as the Internet of Vehicles, sensors, and smartphones, has instigated a new research domain called MBD. At the core of this mobile environment, scalability, cost effectiveness, reliability, analytics, and security are important concerns. Coping with these issues in handling MBD requires understanding the challenges associated with it. Mobile computing and big data have been widely studied separately; however, very few studies have explored the convergence of these two domains. In this article, we critically review recent research efforts directed at MBD. We also classify the MBD by devising a thematic taxonomy that is based on source, analytics, applications, characteristics, security, and data type. Furthermore, we discuss the opportunities offered by MBD in terms of analytics. Some potential uses of MBD in healthcare, telecommunication, digital advertising, and transportation are also presented. Several open research challenges are discussed as future research directions. © 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**

SDN-Based load balancing service for cloud servers

- Abdelaziz, Ahmed, Ahmed, Ejaz, Fong, Ang, Gani, Abdullah, Imran, Muhammad

Authors: Abdelaziz, Ahmed , Ahmed, Ejaz , Fong, Ang , Gani, Abdullah , Imran, Muhammad
Date: 2018
Type: Text , Journal article
Relation: IEEE Communications Magazine Vol. 56, no. 8 (2018), p. 106-111
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Description: With the continuous growth, heterogeneity, and ever increasing demand of services, load balancing of cloud servers is an emerging challenge to meet highly demanding requirements (e.g., data rates, latency, quality of service) of 5G network applications. Although various load balancing techniques have been proposed, some of these techniques either require installation of dedicated additional load balancers for each service, or manual reconfiguration of the device to handle new services is desired. These techniques are expensive, time-consuming, and impractical. Moreover, most of the existing load balancing schemes do not consider service types. This article presents an SDN-based load balancing (SBLB) service for cloud servers to maximize resource utilization and minimize response time of users. The constituents of the proposed scheme are an application module that runs on top of an SDN controller and server pools that connect to the controller through OpenFlow switches. The application module consists of a service classification module, a dynamic load balancing module, and a monitoring module. The controller handles all messages, manages host pools, and maintains the load of host in real time. Experimental results validate the performance of the proposed scheme. Through experimental results, SBLB demonstrates significant decrease in average response time and reply time. © 1979-2012 IEEE.

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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
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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.

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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
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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**

Deep deterministic learning for pattern recognition of different cardiac diseases through the internet of medical things

- Iqbal, Uzair, Wah, Teh, Habib ur Rehman, Muhammad, Mujtaba, Ghulam, Imran, Muhammad, Shoaib, Muhammad

Authors: Iqbal, Uzair , Wah, Teh , Habib ur Rehman, Muhammad , Mujtaba, Ghulam , Imran, Muhammad , Shoaib, Muhammad
Date: 2018
Type: Text , Journal article
Relation: Journal of Medical Systems Vol. 42, no. 12 (2018), p.
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Description: Electrocardiography (ECG) sensors play a vital role in the Internet of Medical Things, and these sensors help in monitoring the electrical activity of the heart. ECG signal analysis can improve human life in many ways, from diagnosing diseases among cardiac patients to managing the lifestyles of diabetic patients. Abnormalities in heart activities lead to different cardiac diseases and arrhythmia. However, some cardiac diseases, such as myocardial infarction (MI) and atrial fibrillation (Af), require special attention due to their direct impact on human life. The classification of flattened T wave cases of MI in ECG signals and how much of these cases are similar to ST-T changes in MI remain an open issue for researchers. This article presents a novel contribution to classify MI and Af. To this end, we propose a new approach called deep deterministic learning (DDL), which works by combining predefined heart activities with fused datasets. In this research, we used two datasets. The first dataset, Massachusetts Institute of Technology–Beth Israel Hospital, is publicly available, and we exclusively obtained the second dataset from the University of Malaya Medical Center, Kuala Lumpur Malaysia. We first initiated predefined activities on each individual dataset to recognize patterns between the ST-T change and flattened T wave cases and then used the data fusion approach to merge both datasets in a manner that delivers the most accurate pattern recognition results. The proposed DDL approach is a systematic stage-wise methodology that relies on accurate detection of R peaks in ECG signals, time domain features of ECG signals, and fine tune-up of artificial neural networks. The empirical evaluation shows high accuracy (i.e., ≤99.97%) in pattern matching ST-T changes and flattened T waves using the proposed DDL approach. The proposed pattern recognition approach is a significant contribution to the diagnosis of special cases of MI. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Improving the security in healthcare information system through elman neural network based classifier

- Al-Dhafian, Buthina, Ahmad, Iftikhar, Hussain, Muhammad, E. Amin, Fazal, Imran, Muhammad

Authors: Al-Dhafian, Buthina , Ahmad, Iftikhar , Hussain, Muhammad , E. Amin, Fazal , Imran, Muhammad
Date: 2017
Type: Text , Journal article
Relation: Journal of Medical Imaging and Health Informatics Vol. 7, no. 6 (2017), p. 1429-1435
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Description: Intrusions are critical issues in information system of healthcare sector because a sole intrusion can cause health issue due to any manipulation in the medical record of the patients. Several intrusion detection (ID) techniques have been used but their performance is the dilemma. The efficiency of intrusion detection systems (IDSs) depends on optimal classifier architecture to categorize the data into intrusive or normal, which required increasing detection rates (DR) and decreasing false alarm rates (FAR). Therefore, to find an optimal classifier architecture to enhance performance in IDSs is an important subject. This study proposed Elman Neural Network-based IDS as classification technique in order to enhance performance. NSL-KDD Dataset is used for evaluation and assessment. Moreover, Principle Component Analysis (PCA) is applied in this work in order to convert raw features to principal space and choose features based on their sensitivity. The proposed approach is capable to enhance performance by increased DR and decreased FAR. © 2017 American Scientific Publishers All rights reserved.

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