Outputs (16)

VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography (2024)
Presentation / Conference Contribution
Khan, M. S., Ahmad, J., Ali, M., Al Dubai, A., Pitropakis, N., & Buchanan, W. J. (2024, July). VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography. Presented at 2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP), Sousse, Tunisia

In this digital era, ensuring the security of data transmission is critically important. Digital data, especially image data, needs to be secured against unauthorized access. In this regards, this paper presents a robust image encryption scheme named... Read More about VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography.

ACNN-IDS: An Attention-Based CNN for Cyberattack Detection in IoT (2024)
Presentation / Conference Contribution
Huma, Z. E., Ahmad, J., Hamadi, H. A., Ghaleb, B., Buchanan, W. J., & Jan, S. U. (2024, February). ACNN-IDS: An Attention-Based CNN for Cyberattack Detection in IoT. Presented at 2024 2nd International Conference on Cyber Resilience (ICCR), Dubai, United Arab Emirates

The Internet of Things (IoT) has become an integral part of modern societies, with devices, networks, and applications offering industrial, economic, and social benefits. However, these devices and networks generate vast amounts of data, making them... Read More about ACNN-IDS: An Attention-Based CNN for Cyberattack Detection in IoT.

SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT (2024)
Journal Article
Alshehri, M. S., Ahmad, J., Almakdi, S., Qathrady, M. A., Ghadi, Y. Y., & Buchanan, W. J. (2024). SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT. IEEE Access, 12, https://doi.org/10.1109/access.2024.3371992

The rise of Internet of Things (IoT) has led to increased security risks, particularly from botnet attacks that exploit IoT device vulnerabilities. This situation necessitates effective Intrusion Detection Systems (IDS), that are accurate, lightweigh... Read More about SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT.

PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks (2023)
Presentation / Conference Contribution
Ali, H., Abubakar, M., Ahmad, J., Buchanan, W. J., & Jaroucheh, Z. (2023, November). PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom

In recent years, there has been a significant proliferation of industrial Internet of Things (IoT) applications, with a wide variety of use cases being developed and put into operation. As the industrial IoT landscape expands, the establishment of se... Read More about PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform (2022)
Journal Article
Ali, H., Ahmad, J., Jaroucheh, Z., Papadopoulos, P., Pitropakis, N., Lo, O., Abramson, W., & Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. https://doi.org/10.3390/e24101379

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro... Read More about Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

Ensemble learning-based IDS for sensors telemetry data in IoT networks (2022)
Journal Article
Naz, N., Khan, M. A., Alsuhibany, S. A., Diyan, M., Tan, Z., Khan, M. A., & Ahmad, J. (2022). Ensemble learning-based IDS for sensors telemetry data in IoT networks. Mathematical Biosciences and Engineering, 19(10), 10550-10580. https://doi.org/10.3934/mbe.2022493

The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with ot... Read More about Ensemble learning-based IDS for sensors telemetry data in IoT networks.

A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map (2022)
Journal Article
Alharbi, A. R., Ahmad, J., Arshad, Shaukat, S., Masood, F., Ghadi, Y. Y., Pitropakis, N., & Buchanan, W. J. (2022). A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map. Complexity, 2022, Article 7047282. https://doi.org/10.1155/2022/7047282

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving... Read More about A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map.

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers (2022)
Presentation / Conference Contribution
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2021, December). Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. Presented at IEEE SINCONF: 14th International Conference on Security of Information and Networks, Edinburgh

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the... Read More about Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers.

Ransomware: Analysing the Impact on Windows Active Directory Domain Services (2022)
Journal Article
McDonald, G., Papadopoulos, P., Pitropakis, N., Ahmad, J., & Buchanan, W. J. (2022). Ransomware: Analysing the Impact on Windows Active Directory Domain Services. Sensors, 22(3), Article 953. https://doi.org/10.3390/s22030953

Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to... Read More about Ransomware: Analysing the Impact on Windows Active Directory Domain Services.

A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT (2021)
Journal Article
Almas Khan, M., Khan, M. A., Ullah Jan, S., Ahmad, J., Jamal, S. S., Shah, A. A., Pitropakis, N., Buchanan, W. J., Alonistioti, N., Panagiotakis, S., & Markakis, E. K. (2021). A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT. Sensors, 21(21), Article 7016. https://doi.org/10.3390/s21217016

A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish–subscribe-based protocol for the communication of sensor or ev... Read More about A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT.

An experimental analysis of attack classification using machine learning in IoT networks (2021)
Journal Article
Churcher, A., Ullah, R., Ahmad, J., Ur Rehman, S., Masood, F., Gogate, M., Alqahtani, F., Nour, B., & Buchanan, W. J. (2021). An experimental analysis of attack classification using machine learning in IoT networks. Sensors, 21(2), Article 446. https://doi.org/10.3390/s21020446

In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT networks can be problematic due to their resource-constrained nature,... Read More about An experimental analysis of attack classification using machine learning in IoT networks.

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.

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.

A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos (2020)
Journal Article
Masood, F., Boulila, W., Ahmad, J., Arshad, A., Sankar, S., Rubaiee, S., & Buchanan, W. J. (2020). A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos. Remote Sensing, 12(11), Article 1893. https://doi.org/10.3390/rs12111893

Aerial photography involves capturing images from aircraft and other flying objects, including Unmanned Aerial Vehicles (UAV). Aerial images are used in many fields and can contain sensitive information that requires secure processing. We proposed an... Read More about A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos.

Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication (2020)
Journal Article
Aziz Shah, S., Ahmad, J., Tahir, A., Ahmed, F., Russell, G., Shah, S. Y., Buchanan, W., & Abbasi, Q. H. (2020). Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication. Micromachines, 11(4), Article 379. https://doi.org/10.3390/mi11040379

Nano-scaled structures, wireless sensing, wearable devices, and wireless communications systems are anticipated to support the development of new next-generation technologies in the near future. Exponential rise in future Radio-Frequency (RF) sensing... Read More about Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication.

An authentication protocol based on chaos and zero knowledge proof (2020)
Journal Article
Major, W., Buchanan, W. J., & Ahmad, J. (2020). An authentication protocol based on chaos and zero knowledge proof. Nonlinear Dynamics, 99, 3065-3087. https://doi.org/10.1007/s11071-020-05463-3

Port Knocking is a method for authenticating clients through a closed stance firewall, and authorising their requested actions, enabling severs to offer services to authenticated clients, without opening ports on the firewall. Advances in port knocki... Read More about An authentication protocol based on chaos and zero knowledge proof.