Convergence of elitist clonal selection algorithm based on martingale theory
- Authors: Hong, Lu , Kamruzzaman, Joarder
- Date: 2013
- Type: Text , Journal article
- Relation: Engineering Letters Vol. 21, no. 4 (2013), p. 181-184
- Full Text: false
- Reviewed:
- Description: In recent years, progress has been made in the analysis of global convergence of clonal selection algorithms (CSA), but most analyses are based on the theory of Markov chain, which depend on the description of the transition matrix and eigenvalues. However, such analyses are very complicated, especially when the population size is large, and are presented for particular implementations of CSA. In this paper, instead of the traditional Markov chain theory, we introduce martingale theory to prove the convergence of a class of CSA, called elitist clonal selection algorithm (ECSA). Using the submartingale convergence theorem, the best individual affinity evolutionary sequence is described as a submartingale, and the almost everywhere convergence of ECSA is derived. Particularly, the algorithm is proved convergent with probability 1 in finite steps when the state space of population is finite. This new proof of global convergence analysis of ECSA is more simplified and effective, and not implementation specific.
Green underwater wireless communications using hybrid optical-acoustic technologies
- Authors: Islam, Kazi , Ahmad, Iftekhar , Habibi, Daryoush , Zahed, M. , Kamruzzaman, Joarder
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Access Vol. 9, no. (2021), p. 85109-85123
- Full Text:
- Reviewed:
- Description: Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology - underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe absorption of light in the medium, the communication range is short in underwater optics. Conversely, acoustics suffers from low data rate and high power consumption, but provides longer communication ranges. Since most underwater equipment relies on battery power, energy-efficient communication is critical for reliable underwater communications. In this work, we derive analytical models for both underwater acoustics and optics, and calculate the required transmit power for reliable communications in various underwater communication environments. We then formulate an optimization problem that minimizes the network power consumption for carrying data from underwater nodes to surface sinks under varying traffic loads and weather conditions. The proposed optimization model can be solved offline periodically, hence the additional computational complexity to find the optimum solution for larger networks is not a limiting factor for practical applications. Our results indicate that the proposed technique yields up to 35% power savings compared to existing opto-acoustic solutions. © 2013 IEEE.
A robust forgery detection method for copy-move and splicing attacks in images
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
- Date: 2020
- Type: Text , Journal article
- Relation: Electronics Vol. 9, no. 9 (2020), p. 1-22
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) image sensors, social media, and smartphones generate huge volumes of digital images every day. Easy availability and usability of photo editing tools have made forgery attacks, primarily splicing and copy-move attacks, effortless, causing cybercrimes to be on the rise. While several models have been proposed in the literature for detecting these attacks, the robustness of those models has not been investigated when (i) a low number of tampered images are available for model building or (ii) images from IoT sensors are distorted due to image rotation or scaling caused by unwanted or unexpected changes in sensors' physical set-up. Moreover, further improvement in detection accuracy is needed for real-word security management systems. To address these limitations, in this paper, an innovative image forgery detection method has been proposed based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) and a new feature extraction method using the mean operator. First, images are divided into non-overlapping fixed size blocks and 2D block DCT is applied to capture changes due to image forgery. Then LBP is applied to the magnitude of the DCT array to enhance forgery artifacts. Finally, the mean value of a particular cell across all LBP blocks is computed, which yields a fixed number of features and presents a more computationally efficient method. Using Support Vector Machine (SVM), the proposed method has been extensively tested on four well known publicly available gray scale and color image forgery datasets, and additionally on an IoT based image forgery dataset that we built. Experimental results reveal the superiority of our proposed method over recent state-of-the-art methods in terms of widely used performance metrics and computational time and demonstrate robustness against low availability of forged training samples.
- Description: This research was funded by Research Priority Area (RPA) scholarship of Federation University Australia.
Measuring trustworthiness of IoT image sensor data using other sensors' complementary multimodal data
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 775-780
- Full Text: false
- Reviewed:
- Description: Trust of image sensor data is becoming increasingly important as the Internet of Things (IoT) applications grow from home appliances to surveillance. Up to our knowledge, there exists only one work in literature that estimates trustworthiness of digital images applied to forensic applications, based on a machine learning technique. The efficacy of this technique is heavily dependent on availability of an appropriate training set and adequate variation of IoT sensor data with noise, interference and environmental condition, but availability of such data cannot be assured always. Therefore, to overcome this limitation, a robust method capable of estimating trustworthy measure with high accuracy is needed. Lowering cost of sensors allow many IoT applications to use multiple types of sensors to observe the same event. In such cases, complementary multimodal data of one sensor can be exploited to measure trust level of another sensor data. In this paper, for the first time, we introduce a completely new approach to estimate the trustworthiness of an image sensor data using another sensor's numerical data. We develop a theoretical model using the Dempster-Shafer theory (DST) framework. The efficacy of the proposed model in estimating trust level of an image sensor data is analyzed by observing a fire event using IoT image and temperature sensor data in a residential setup under different scenarios. The proposed model produces highly accurate trust level in all scenarios with authentic and forged image data. © 2019 IEEE.
- Description: E1
Passive detection of splicing and copy-move attacks in image forgery
- Authors: Islam, Mohammad , Kamruzzaman, Joarder , Karmakar, Gour , Murshed, Manzur , Kahandawa, Gayan
- Date: 2018
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th International Conference on Neural Information Processing, ICONIP 2018; Siem Reap, Cambodia; 13th-16th December 2018; published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11304 LNCS, p. 555-567
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) image sensors for surveillance and monitoring, digital cameras, smart phones and social media generate huge volume of digital images every day. Image splicing and copy-move attacks are the most common types of image forgery that can be done very easily using modern photo editing software. Recently, digital forensics has drawn much attention to detect such tampering on images. In this paper, we introduce a novel feature extraction technique, namely Sum of Relevant Inter-Cell Values (SRIV) using which we propose a passive (blind) image forgery detection method based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP). First, the input image is divided into non-overlapping blocks and 2D block DCT is applied to capture the changes of a tampered image in the frequency domain. Then LBP operator is applied to enhance the local changes among the neighbouring DCT coefficients, magnifying the changes in high frequency components resulting from splicing and copy-move attacks. The resulting LBP image is again divided into non-overlapping blocks. Finally, SRIV is applied on the LBP image blocks to extract features which are then fed into a Support Vector Machine (SVM) classifier to identify forged images from authentic ones. Extensive experiment on four well-known benchmark datasets of tampered images reveal the superiority of our method over recent state-of-the-art methods.
Detecting splicing and copy-move attacks in color images
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur , Kahandawa, Gayan , Parvin, Nahida
- Date: 2018
- Type: Text , Conference proceedings
- Relation: 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018; Canberra, Australia; 10th-13th December 2018 p. 1-7
- Full Text:
- Reviewed:
- Description: Image sensors are generating limitless digital images every day. Image forgery like splicing and copy-move are very common type of attacks that are easy to execute using sophisticated photo editing tools. As a result, digital forensics has attracted much attention to identify such tampering on digital images. In this paper, a passive (blind) image tampering identification method based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) has been proposed. First, the chroma components of an image is divided into fixed sized non-overlapping blocks and 2D block DCT is applied to identify the changes due to forgery in local frequency distribution of the image. Then a texture descriptor, LBP is applied on the magnitude component of the 2D-DCT array to enhance the artifacts introduced by the tampering operation. The resulting LBP image is again divided into non-overlapping blocks. Finally, summations of corresponding inter-cell values of all the LBP blocks are computed and arranged as a feature vector. These features are fed into a Support Vector Machine (SVM) with Radial Basis Function (RBF) as kernel to distinguish forged images from authentic ones. The proposed method has been experimented extensively on three publicly available well-known image splicing and copy-move detection benchmark datasets of color images. Results demonstrate the superiority of the proposed method over recently proposed state-of-the-art approaches in terms of well accepted performance metrics such as accuracy, area under ROC curve and others.
- Description: 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018
Decentralized content sharing among tourists in visiting hotspots
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
- Date: 2017
- Type: Text , Journal article
- Relation: Journal of Network and Computer Applications Vol. 79, no. (2017), p. 25-40
- Full Text:
- Reviewed:
- Description: Content sharing with smart mobile devices using decentralized approach enables users to share contents without the use of any fixed infrastructure, and thereby offers a free-of-cost platform that does not add to Internet traffic which, in its current state, is approaching bottleneck in its capacity. Most of the existing decentralized approaches in the literature consider spatio-temporal regularity in human movement patterns and pre-existing social relationship for the sharing scheme to work. However, such predictable movement patterns and social relationship information are not available in places like tourist spots where people visit only for a short period of time and usually meet strangers. No works exist in literature that deals with content sharing in such environment. In this work, we propose a content sharing approach for such environments. The group formation mechanism is based on users' interest score and stay probability in the individual region of interest (ROI) as well as on the availability and delivery probabilities of contents in the group. The administrator of each group is selected by taking into account its probability of stay in the ROI, connectivity with other nodes, its trustworthiness and computing and energy resources to serve the group. We have also adopted an incentive mechanism as encouragement that awards nodes for sharing and forwarding contents. We have used network simulator NS3 to perform extensive simulation on a popular tourist spot in Australia which facilitates a number of activities. The proposed approach shows promising results in sharing contents among tourists, measured in terms of content hit, delivery success rate and latency.
- Description: Content sharing with smart mobile devices using decentralized approach enables users to share contents without the use of any fixed infrastructure, and thereby offers a free-of-cost platform that does not add to Internet traffic which, in its current state, is approaching bottleneck in its capacity. Most of the existing decentralized approaches in the literature consider spatio-temporal regularity in human movement patterns and pre-existing social relationship for the sharing scheme to work. However, such predictable movement patterns and social relationship information are not available in places like tourist spots where people visit only for a short period of time and usually meet strangers. No works exist in literature that deals with content sharing in such environment. In this work, we propose a content sharing approach for such environments. The group formation mechanism is based on users' interest score and stay probability in the individual region of interest (ROI) as well as on the availability and delivery probabilities of contents in the group. The administrator of each group is selected by taking into account its probability of stay in the ROI, connectivity with other nodes, its trustworthiness and computing and energy resources to serve the group. We have also adopted an incentive mechanism as encouragement that awards nodes for sharing and forwarding contents. We have used network simulator NS3 to perform extensive simulation on a popular tourist spot in Australia which facilitates a number of activities. The proposed approach shows promising results in sharing contents among tourists, measured in terms of content hit, delivery success rate and latency. © 2016
Carry me if you can : A utility based forwarding scheme for content sharing in tourist destinations
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
- Date: 2016
- Type: Text , Conference proceedings
- Relation: 22nd Asia-Pacific Conference on Communications, APCC 2016; Yogyakarta, Indonesia; 25th-27th August 2016 p. 261-267
- Full Text:
- Reviewed:
- Description: Message forwarding is an integral part of the decentralized content sharing process as the content delivery success highly depends on it. Existing literature employs spatio-temporal regularity of human movement pattern and pre-existing social relationship to take message forwarding decisions. However, such approaches are ineffectual in environments where those information are unavailable such as a tourist spot or camping site. In this study, we explore the message forwarding techniques in such environments considering the information that are readily available and can be gathered on the fly. We propose a utility based forwarding scheme to select the appropriate forwarder node based on co-location stay time, connectivity and available resources. A higher co-location stay time reflects that the forwarder and the destination node is likely to have more opportunistic contacts, while the connectivity and available resource ensure that the selected forwarder has sufficient neighbours and resources to carry the message forward. Simulation results suggest that the proposed approach attains high hit and success rate and low latency for successful content delivery, which is comparable to those proposed for work-place type scenarios with regular movement pattern and pre-existing relationships. © 2016 IEEE.
Content exchange among mobile tourists using users' interest and place-centric activities
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
- Date: 2015
- Type: Text , Conference paper
- Relation: 2015 10th International Conference on Information, Communications and Signal Processing (Icics); Singapore, Singapore; 2nd-4th December 2015 p. 1-5
- Full Text: false
- Reviewed:
- Description: In this work we investigate decentralized content exchange among tourists who are mostly strangers, depicts irregular movement patterns and most likely not to have any prior social relationship or difficult to establish any in a tourist spot. We incorporate user's interest, trustworthy online recommendations, and place-centric information to facilitate content exchange in such tourist destinations. The proposed administrator selection policy considers stay probability in activities, connectivity among nodes and their available resources. We have done extensive simulation using network simulator NS3 on a popular tourist spot in Australia that provides a number of activities. Our proposed approach shows promising results in exchanging contents among users measured in terms of content hit and delivery success rate as well as latency. The success rate is comparable to those reported in the literature for cases where social relationship exist and nodes follow regular predictable movement patterns.
Content sharing among visitors with irregular movement patterns in visiting hotspots
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal
- Date: 2015
- Type: Text , Conference paper
- Relation: 2015 IEEE 14th International Symposium on Network Computing and Applications (NCA); Cambridge, United States; 28th - 30th September 2015; published in Proceedings - 2015 IEEE 14th International Symposium on Network Computing and Applications, NCA 2015 p. 230-234
- Full Text: false
- Reviewed:
- Description: Smart mobile devices have become immensely popular among the people worldwide and provide a new platform for generating and sharing contents. The centralized and hybrid architectures for content sharing require constant Internet connection, increase traffic and incur costs. To address these issues several content sharing approaches have been proposed using the decentralized architecture. Most of the proposed approaches use spatio-temporal regularity and pre-existing social relationships of the users to predict their movements and facilitate content sharing. However, there are scenarios such as visiting hotspots where regular movement patterns or established social relationships among people might not exist. Content sharing in such scenarios has not been addressed yet in literature and existing prediction based approaches are ineffectual. This study focuses on facilitating content sharing in the afore-mentioned scenarios. We take account of user interests, recommendations from on-line social networks, hotspot specific activities and other relevant information to construct communities which facilitate content sharing. For each community an administrator, who maintains content and member lists and render directory services, is selected based on stay probability, interest score, battery lifetime and device configuration. Simulation results show that our proposed approach attains high content hit and success rate and low latency in delivery which is nearly comparable to those proposed for scenarios with regular predictable movement patterns reported in literature.
A dynamic content distribution scheme for decentralized sharing in tourist hotspots
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Network and Computer Applications Vol. 129, no. (2019), p. 9-24
- Full Text:
- Reviewed:
- Description: Decentralized content sharing (DCS) is emerging as a suitable platform for smart mobile device users to generate and share contents seamlessly without the requirement of a centralized server. This feature is particularly important for places that lack Internet coverage such as tourist attractions where users can form an ad-hoc network and communicate opportunistically to share contents. Existing DCS approaches when applied for such type of places suffer from low delivery success rate and high latency. Although a handful of recent approaches have specifically targeted improvement of content delivery service in tourist spot like scenario, these and other DCS approaches do not focus on contents’ demand and supply which vary considerably due to visitor in-and-out flow and occurrence of influencing events. This is further compounded by the lack of any content distribution (replication) scheme. The content delivery service will be improved if contents can be proactively distributed in strategic positions based on dynamic demand and supply and medium access contention. In this paper, we propose a dynamic content distribution scheme (DCDS) considering these practical issues for sharing contents in tourist attractions. Simulation results show that the proposed approach significantly improves (7
Wireless security and privacy issues
- Authors: Kamruzzaman, Joarder
- Date: 2008
- Type: Text , Book chapter
- Relation: Mobile Multimedia Communications: Concepts, Applications and Challenges p. 237-247
- Full Text: false
- Reviewed:
Dynamic content distribution for decentralized sharing in tourist spots using demand and supply
- Authors: Kamruzzaman, Joarder , Karmakar, Gour , Gondal, Iqbal , Kaisar, Shahriar
- Date: 2017
- Type: Text , Conference proceedings
- Relation: 13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017; Valencia, Spain; 26th-30th June 2016 p. 2121-2126
- Full Text: false
- Reviewed:
- Description: Decentralized content sharing (DCS) is emerging as an important platform for sharing contents among smart mobile device users, where devices form an ad-hoc network and communicate opportunistically. Existing DCS approaches for tourist spot like scenarios achieve low delivery success rate and high latency as they do not focus on dynamic demand for contents which usually vary considerably with the number of visitors present or occurrence of some influencing events. The amount of available supply also changes because of the nodes leaving the area. Only way to improve content delivery service is to distribute the contents in strategic positions based on dynamic demand and supply. In this paper, we propose a dynamic content distribution (DCD) method considering dynamic demand and supply for contents in tourist spots. Simulation results validate the improvement of the proposed approach. © 2017 IEEE.
- Description: 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
Security and privacy issues in RFID systems
- Authors: Kamruzzaman, Joarder , Azad, Arman , Karmakar, Nemai , Karmakar, Gour , Srinivasan, Bala
- Date: 2012
- Type: Text , Book chapter
- Relation: Advanced RFID Systems, Security, and Applications Chapter 2 p. 16-40
- Full Text: false
- Reviewed:
- Description: Security and privacy protection are very critical requirements for the widespread deployment of RFID technologies for commercial applications. In this chapter, the authors first present the security and privacy requirement of any commercial system, and then highlight the security and privacy threats that are unique to an RFID system. The security and privacy preserving protocols for RFID system proposed in literature are elaborately discussed, analyzing their strengths, vulnerabilities, and implementation issues. The open research challenges that need further investigation, especially with the rapid introduction of diverse RFID applications, are also presented.
Object analysis with visual sensors and RFID
- Authors: Karmakar, Gour , Karmakar, Nemai , Dooley, Laurence , Kamruzzaman, Joarder
- Date: 2013
- Type: Text , Book chapter
- Relation: Image Processing: Concepts, Methodologies, Tools, and Applications p. 1492-1507
- Full Text: false
- Reviewed:
- Description: Object analysis using visual sensors is one of the most important and challenging issues in computer vision research due principally to difficulties in object representation, segmentation, and recognition within a general framework. This has motivated researchers to investigate exploiting the potential identification capability of RFID (radio frequency identification) technology for object analysis. RFID however, has a number of fundamental limitations including a short sensing range, missing tag detection, not working for all objects, and some items being just too small to be tagged. This has meant applying RFID alone has not been entirely effective in computer vision applications. To address these restrictions, object analysis approaches based on a combination of visual sensors and RFID have recently been successfully introduced. This chapter presents a contemporary review on these object analysis techniques for localisation, tracking, and object and activity recognition, together with some future research directions in this burgeoning field. © 2013, IGI Global.
Object analysis with visual sensors and RFID
- Authors: Karmakar, Gour , Dooley, Laurence , Karmakar, Nemai , Kamruzzaman, Joarder
- Date: 2012
- Type: Text , Book chapter
- Relation: Chipless and conventional radio frequency identification : Systems for ubiquitous tagging Chapter 12 p. 234-250
- Full Text: false
- Reviewed:
- Description: Object analysis using visual sensors is one of the most important and challenging issues in computer vision research due principally to difficulties in object representation, segmentation, and recognition within a general framework. This has motivated researchers to investigate exploiting the potential identification capability of RFID (radio frequency identification) technology for object analysis. RFID however, has a number of fundamental limitations including a short sensing range, missing tag detection, not working for all objects, and some items being just too small to be tagged. This has meant applying RFID alone has not been entirely effective in computer vision applications. To address these restrictions, object analysis approaches based on a combination of visual sensors and RFID have recently been successfully introduced. This chapter presents a contemporary review on these object analysis techniques for localisation, tracking, and object and activity recognition, together with some future research directions in this burgeoning field.
IoT Sensor Numerical Data Trust Model Using Temporal Correlation
- Authors: Karmakar, Gour , Das, Rajkumar , Kamruzzaman, Joarder
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Internet of Things Journal Vol. 7, no. 4 (2020), p. 2573-2581
- Full Text: false
- Reviewed:
- Description: Internet of Things (IoT) applications are increasingly being adopted for innovative and cost-effective services. However, the IoT devices and data are susceptible to various attacks, including cyberattacks, which emphasizes the need for pervasive security measure like trust evaluation on the fly. There exist several IoT numerical data trustworthiness measures which are based on the quality of information (QoI) and correlations. The QoI measurement techniques excessively exploit heuristics, while the correlation-based approaches predict temporal correlation using an average or moving average, which limits their efficacy. To improve accuracy and reliability, we propose a model for assessing trust of IoT sensor numerical data by representing the temporal correlation using temporal relationship. We represent the temporal relationship between data within a time window in two ways: first, using the discrete cosine transform (DCT) coefficients of daily data; and second, to obtain the impact of shuttle variation, we further divide the daily data into some time windows and calculate the average of each DCT coefficient over all time windows. These two feature sets are then used to develop two independent deep neural network models. The model outcomes are fused by the Dempster-Shepard theory to calculate trust scores. The strength of our model is evaluated using both trustworthy and untrustworthy data - the former are collected from sensors under controlled supervision in a smart city project in Melbourne, Australia and the latter are generated either by simulating breached sensors or perturbing real data. Our proposed approach outperforms a contemporary correlation-based approach in terms of trust score accuracy and consistency. © 2014 IEEE.
A smart priority-based traffic control system for emergency vehicles
- Authors: Karmakar, Gour , Chowdhury, Abdullahi , Kamruzzaman, Joarder , Gondal, Iqbal
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 21, no. 14 (2021), p. 15849-15858
- Full Text: false
- Reviewed:
- Description: Unwanted events on roads, such as incidents and increased traffic jams, can cause human lives and economic loss. For efficient incident management, it is essential to send Emergency Vehicles (EVs) to the incident place as quickly as possible. To reduce incidence clearance time, several approaches exist to provide a clear pathway to EVs mainly fitted with RFID sensors in the urban areas. However, they neither assign priority to the EVs based on the type and severity of an incident nor consider the effect on other on-road traffic. To address this issue, in this paper, we introduce an Emergency Vehicle Priority System (EVPS) by determining the priority level of an EV based on the type and the severity of an incident, and estimating the number of necessary signal interventions while considering the impact of those interventions on the traffic in the roads surrounding the EV's travel path. We present how EVPS determines the priority code and a new algorithm to estimate the number of green signal interventions to attain the quickest incident response while concomitantly reducing impact on others. A simulation model is developed in Simulation of Urban Mobility (SUMO) using the real traffic data of Melbourne, Australia, captured by various sensors. Results show that our system recommends appropriate number of intervention that can reduce emergency response time significantly. © 2001-2012 IEEE.
An efficient data delivery mechanism for AUV-based Ad hoc UASNs
- Authors: Karmakar, Gour , Kamruzzaman, Joarder , Nowsheen, Nusrat
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 86, no. (2018), p. 1193-1208
- Full Text: false
- Reviewed:
- Description: Existing 3D Underwater Acoustic Sensor Networks (UASNs) are either fixed having nodes anchored with the seabed or a combination of Autonomous Underwater Vehicles (AUVs) and a fixed UASN where AUVs are controlled to move along paths for data collection. Existing data delivery protocols for such AUV equipped networks are designed in a way where AUVs act as message ferries. These UASNs are deployed for a specific service such as asset (e.g., oil pipes, shipwreck) monitoring and event detection. For a coordinated data collection, to deploy a network for any service like information discovery in an ad hoc manner, it requires a 3D UASN consisting of only AUVs and the movement of an AUV needs to be controlled by another AUV through commands. To our knowledge, no such data delivery protocol required for a 3D UASN comprising only AUVs exists in the current literature that can efficiently handle data collection and delivery. To address this research gap, in this paper, an AUV-based technique for ad hoc underwater network, namely AUV-based Data Delivery Protocol (ADDP), is introduced which ensures data delivery within a given time-constraint by controlling node (i.e., AUV) movement at each hop through commands of a node. The performance of the proposed protocol has also been evaluated and compared with existing relevant protocols in terms of packet delivery ratio, routing overhead and energy consumption considering various network scenarios and sizes. Results exhibit outstanding performance improvement achieved by the proposed protocol for all metrics. © 2017 Elsevier B.V.
Assessing trust level of a driverless car using deep learning
- Authors: Karmakar, Gour , Chowdhury, Abdullahi , Das, Rajkumar , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 22, no. 7 (2021), p. 4457-4466
- Full Text: false
- Reviewed:
- Description: The increasing adoption of driverless cars already providing a shift to move away from traditional transportation systems to automated ones in many industrial and commercial applications. Recent research has justified that driverless vehicles will considerably reduce traffic congestions, accidents, carbon emissions, and enhance the accessibility of driving to wider cross-section of people and lifestyle choices. However, at present, people's main concerns are about its privacy and security. Since traditional protocol layers based security mechanisms are not so effective for a distributed system, trust value-based security mechanisms, a type of pervasive security, are appearing as popular and promising techniques. A few statistical non-learning based models for measuring the trust level of a driverless are available in the current literature. These are not so effective because of not being able to capture the extremely distributed, dynamic, and complex nature of the traffic systems. To bridge this research gap, in this paper, for the first time, we propose two deep learning-based models that measure the trustworthiness of a driverless car and its major On-Board Unit (OBU) components. The second model also determines its OBU components that were breached during the driving operation. Results produced using real and simulated traffic data demonstrate that our proposed DNN based deep learning models outperform other machine learning models in assessing the trustworthiness of individual car as well as its OBU components. The average precision of detection accuracies for the car, LiDAR, camera, and radar are 0.99, 0.96, 0.81, and 0.83, respectively, which indicates the potential real-life application of our models in assessing the trust level of a driverless car. © 2000-2011 IEEE.