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Outputs (682)

FPC-BI: Fast Probabilistic Consensus within Byzantine Infrastructures (2020)
Journal Article
Popov, S., & Buchanan, W. J. (2021). FPC-BI: Fast Probabilistic Consensus within Byzantine Infrastructures. Journal of Parallel and Distributed Computing, 147, 77-86. https://doi.org/10.1016/j.jpdc.2020.09.002

This paper presents a novel leaderless protocol (FPC-BI: Fast Probabilistic Consensus within Byzantine Infrastructures) with a low communicational complexity and which allows a set of nodes to come to a consensus on a value of a single bit. The paper... Read More about FPC-BI: Fast Probabilistic Consensus within Byzantine Infrastructures.

Machine Learning-driven Optimization for Intrusion Detection in Smart Vehicular Networks (2020)
Journal Article
Alsarhan, A., Al-Ghuwairi, A., Almalkaw, I., Alauthman, M., & Al-Dubai, A. (2021). Machine Learning-driven Optimization for Intrusion Detection in Smart Vehicular Networks. Wireless Personal Communications, 117, 3129-3152 (2021). https://doi.org/10.1007/s11277-020-07797-y

An essential element in the smart city vision is providing safe and secure journeys via intelligent vehicles and smart roads. Vehicular ad hoc networks (VANETs) have played a significant role in enhancing road safety where vehicles can share road inf... Read More about Machine Learning-driven Optimization for Intrusion Detection in Smart Vehicular Networks.

Tuft: Tree Based Heuristic Data Dissemination for Mobile Sink Wireless Sensor Networks (2020)
Journal Article
Busaileh, O., Hawbani, A., Xingfu, W., Liu, P., Zhao, L., & Al-Dubai, A. (2022). Tuft: Tree Based Heuristic Data Dissemination for Mobile Sink Wireless Sensor Networks. IEEE Transactions on Mobile Computing, 21(4), 1520-1536. https://doi.org/10.1109/TMC.2020.3022403

Wireless sensor networks (WSNs) with a static sink suffer from concentrated data traffic in the vicinity of the sink, which increases the burden on the nodes surrounding the sink, and impels them to deplete their batteries faster than other nodes in... Read More about Tuft: Tree Based Heuristic Data Dissemination for Mobile Sink Wireless Sensor Networks.

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples (2020)
Presentation / Conference Contribution
Babaagba, K., Tan, Z., & Hart, E. (2020, July). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. Presented at The 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020), Glasgow, UK

Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t... Read More about Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples.

DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption (2020)
Journal Article
Khan, J. S., Boulila, W., Ahmad, J., Rubaiee, S., Rehman, A. U., Alroobaea, R., & Buchanan, W. J. (2020). DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption. IEEE Access, 8, 159732-159744. https://doi.org/10.1109/access.2020.3020917

Visual selective image encryption can both improve the efficiency of the image encryption algorithm and reduce the frequency and severity of attacks against data. In this article, a new form of encryption is proposed based on keys derived from Deoxyri... Read More about DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption.

Evaluation of Ensemble Learning for Android Malware Family Identification (2020)
Journal Article
Wylie, J., Tan, Z., Al-Dubai, A., & Wang, J. (2020). Evaluation of Ensemble Learning for Android Malware Family Identification. Journal of Guangzhou University (Natural Science Edition), 19(4), 28-41

Every Android malware sample generally belongs to a specific family that performs a similar set of actions and characteristics. Having the ability to effectively identify Android malware families can assist in addressing the damage caused by malware.... Read More about Evaluation of Ensemble Learning for Android Malware Family Identification.

Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment (2020)
Journal Article
Zhao, L., Huang, H., Su, C., Ding, S., Huang, H., Tan, Z., & Li, Z. (2021). Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment. IEEE Internet of Things Journal, 8(5), 3211-3223. https://doi.org/10.1109/jiot.2020.3019732

Device-free localization (DFL) locates targets without equipping with wireless devices or tag under the Internet-of-Things (IoT) architectures. As an emerging technology, DFL has spawned extensive applications in IoT environment, such as intrusion de... Read More about Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment.

FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture (2020)
Journal Article
Song, J., Zhong, Q., Su, C., Tan, Z., & Liu, Y. (2021). FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture. IEEE Sensors Journal, 21(16), 17430-17438. https://doi.org/10.1109/JSEN.2020.3017695

Food security is a global concern. Benefit from the development of 5G, IoT is used in agriculture to help the farmers to maintain and improve productivity. It not only enables the customers, both at home and abroad, to become more informed about the... Read More about FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture.

Trust-based Ecosystem to Combat Fake News (2020)
Presentation / Conference Contribution
Jaroucheh, Z., Alissa, M., & Buchanan, W. J. (2020, May). Trust-based Ecosystem to Combat Fake News. Presented at 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), Toronto, ON, Canada

The growing spread of misinformation and dis-information has grave political, social, ethical, and privacy implications for society. Therefore, there is an ethical need to combat the flow of fake news. This paper attempts to resolves some of the aspe... Read More about Trust-based Ecosystem to Combat Fake News.

Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution (2020)
Journal Article
Qayyum, A., Ahmad, J., Boulila, W., Rubaiee, S., Arshad, Masood, F., Khan, F., & Buchanan, W. J. (2020). Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution. IEEE Access, 8, 140876-140895. https://doi.org/10.1109/access.2020.3012912

The evolution of wireless and mobile communication from 0G to the upcoming 5G gives riseto data sharing through the Internet. This data transfer via open public networks are susceptible to severaltypes of attacks. Encryption is a method that can prot... Read More about Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution.

Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment (2020)
Presentation / Conference Contribution
Chacon, J., Mckeown, S., & Macfarlane, R. (2020, June). Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2020), Dublin, Ireland

Attacks by Advanced Persistent Threats (APTs) have been shown to be difficult to detect using traditional signature-and anomaly-based intrusion detection approaches. Deception techniques such as decoy objects, often called honey items, may be deploye... Read More about Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques - An Experiment.

5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum (2020)
Presentation / Conference Contribution
Khan, J. S., Tahir, A., Ahmad, J., Shah, S. A., Abbasi, Q. H., Russell, G., & Buchanan, W. (2020, July). 5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum. Presented at 2020 Computing Conference, London

Freezing of gait (FOG) is one of the most incapacitating and disconcerting symptom in Parkinson's disease (PD). FOG is the result of neural control disorder and motor impairments, which severely impedes forward locomotion. This paper presents the exp... Read More about 5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum.

Decentralized Accessibility of e-commerce Products through Blockchain Technology (2020)
Journal Article
Kumar, G., Saha, R., Buchanan, W. J., Geetha, G., Thomas, R., Rai, M. K., Kim, T., & Alazab, M. (2020). Decentralized Accessibility of e-commerce Products through Blockchain Technology. Sustainable Cities and Society, 62, Article 102361. https://doi.org/10.1016/j.scs.2020.102361

A distributed and transparent ledger system is considered for various \textit{e}-commerce products including health medicines, electronics, security appliances, food products and many more to ensure technological and e-commerce sustainability. This s... Read More about Decentralized Accessibility of e-commerce Products through Blockchain Technology.

Testing And Hardening IoT Devices Against the Mirai Botnet (2020)
Presentation / Conference Contribution
Kelly, C., Pitropakis, N., McKeown, S., & Lambrinoudakis, C. (2020, June). Testing And Hardening IoT Devices Against the Mirai Botnet. Presented at IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2020), Dublin, Ireland

A large majority of cheap Internet of Things (IoT) devices that arrive brand new, and are configured with out-of-the-box settings, are not being properly secured by the manufactures, and are vulnerable to existing malware lurking on the Internet. Amo... Read More about Testing And Hardening IoT Devices Against the Mirai Botnet.

Deep learning based emotion analysis of microblog texts (2020)
Journal Article
Xu, D., Tian, Z., Lai, R., Kong, X., Tan, Z., & Shi, W. (2020). Deep learning based emotion analysis of microblog texts. Information Fusion, 64, 1-11. https://doi.org/10.1016/j.inffus.2020.06.002

Traditional text emotion analysis methods are primarily devoted to studying extended texts, such as news reports and full-length documents. Microblogs are considered short texts that are often characterized by large noises, new words, and abbreviatio... Read More about Deep learning based emotion analysis of microblog texts.

Evaluation of Live Forensic Techniques in Ransomware Attack Mitigation (2020)
Journal Article
Davies, S. R., Macfarlane, R., & Buchanan, W. J. (2020). Evaluation of Live Forensic Techniques in Ransomware Attack Mitigation. Forensic Science International: Digital Investigation, 33, Article 300979. https://doi.org/10.1016/j.fsidi.2020.300979

Ransomware continues to grow in both scale, cost, complexity and impact since its initial discovery nearly 30 years ago. Security practitioners are engaged in a continual "arms race" with the ransomware developers attempting to defend their digital i... Read More about Evaluation of Live Forensic Techniques in Ransomware Attack Mitigation.

CASCF: Certificateless Aggregated SignCryption Framework for Internet-of-Things Infrastructure (2020)
Journal Article
Kim, T., Kumar, G., Saha, R., Alazab, M., Buchanan, W. J., Rai, M. K., Geetha, G., & Thomas, R. (2020). CASCF: Certificateless Aggregated SignCryption Framework for Internet-of-Things Infrastructure. IEEE Access, 8, 94748-94756. https://doi.org/10.1109/access.2020.2995443

The increasing number of devices in the age of Internet-of-Thing (IoT) has arisen a number of problems related to security. Cryptographic processes, more precisely the signatures and the keys, increase and generate an overhead on the network resource... Read More about CASCF: Certificateless Aggregated SignCryption Framework for Internet-of-Things Infrastructure.

A Privacy-Preserving Secure Framework for Electric Vehicles in IoT using Matching Market and Signcryption (2020)
Journal Article
Kumar, G., Rai, M., Saha, R., Buchanan, W. J., Thomas, R., Geetha, G., Kim, T., & Rodrigues, J. (2020). A Privacy-Preserving Secure Framework for Electric Vehicles in IoT using Matching Market and Signcryption. IEEE Transactions on Vehicular Technology, 69(7), 7707-7722. https://doi.org/10.1109/tvt.2020.2989817

The present world of vehicle technology is inclined to develop Electric Vehicles (EVs) with various optimized features. These vehicles need frequent charging which takes a longer time to charge up. Therefore, scheduling of vehicles in charging statio... Read More about A Privacy-Preserving Secure Framework for Electric Vehicles in IoT using Matching Market and Signcryption.

A Novel Multimodal Collaborative Drone-Assisted VANET Networking Model (2020)
Journal Article
Lin, N., Fu, L., Zhao, L., Min, G., Al-Dubai, A., & Gacanin, H. (2020). A Novel Multimodal Collaborative Drone-Assisted VANET Networking Model. IEEE Transactions on Wireless Communications, 19(7), 4919-4933. https://doi.org/10.1109/TWC.2020.2988363

Drones can be used in many assistance roles in complex communication situations and play key roles as aerial wireless relays to help terrestrial network communications. Although a great deal of emphasis has been placed on the drone-assisted networks,... Read More about A Novel Multimodal Collaborative Drone-Assisted VANET Networking Model.