Internet Commerce Security Laboratory (ICSL)

• AI-based de-obfuscation of malware
• AI-generated cyber training range scenarios
• Reinforcement learning for automated cyber operations (ACO)
• Intelligent honeypots for threat detection
• AI prompt engineering for cybersecurity applications
• Adversarial attacks on malware analysis systems
• Insider threat detection
• Blockchain-based grain traceability systems
• Alert correlation for Security Operations Centre (SOC) operations

• Malware reverse engineering
• Phishing site authorship attribution
• Power grid security analysis
• Malware similarity analysis
• Detection of malware network traffic
• Automated identification of child abuse images
• Credit card fraud detection
• Analysis and detection of android malware

• An AI-enabled cybersecurity trainer for small business. ECR Seed Funding. 2025. ($7,000)
• Classification of code modifications to differentiate security fixes and learn vulnerable code patterns in compiled software. AI4DM. 2022. ($30,000)
• AI for penetration testing phase 2. AI4DM. 2021. ($50,000)
• AI for penetration testing phase 1. AI4DM. 2020. ($20,000) 

2024

• Mishra, P., Black, P., Bagirov, A., & Pang, S. (2024). Discriminating Malware Families using Partitional Clustering. In 2024 IEEE 23rd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 2256-2261). IEEE.

2021

• Black P., Gondal I., Brooks R., Yu L., AFES: An Advanced Forensic Evidence System. (AI-PLE 2021), IEEE.
• Black P., Gondal I., Cross Compiler Bipartite Vulnerability Search, (Electronics Journal 2021).
• Black P., Gondal I., Baghirov, A., Moniruzzaman Md., Malware Variant Identification Using Incremental Clustering, (Electronics Journal, 2021).
• Khoda, M. E., Kamruzzaman, J., Gondal, I., Imam, T., & Rahman, A. (2021). Malware detection in edge devices with fuzzy oversampling and dynamic class weighting. Applied Soft Computing, 112, 107783.
• Uddin, M. A., Stranieri, A., Gondal, I., & Balasubramanian, V. (2021). A survey on the adoption of blockchain in iot: Challenges and solutions. Blockchain: Research and Applications, 2(2), 100006.

2020

• Black P., Gondal I., Vamplew P., and Lakhotia A., Identifying Cross-Version Function Similarity Using Contextual Features (Trustcom 2020).
• Black P., Gondal I., Vamplew P., and Lakhotia A., Function Similarity Using Family Context (Electronics Journal 2020).
• Black P., Sohail A., Gondal I., Kamruzzaman, J., Vamplew P., Watters, P., API Based Discrimination of Ransomware and Benign Cryptographic Programs, (ICONIP 2020).
• Black P., Gondal I., Vamplew P., and Lakhotia A., Reanimating Historic Malware Samples, book chapter in Malware Analysis using Artificial Intelligence and Deep Learning, Springer 2020.
• Khraisat, A.; Gondal, I.; Vamplew, P.; Kamruzzaman, J.; Alazab, A., “Hybrid Intrusion Detection System Based on the Stacking Ensemble of C5 Decision Tree Classifier and One Class Support Vector Machine”, Electronics Journal, 9, 173. Impact factor: 1.754, 2020
• Md. Ashraf Uddin, Andrew Stranieri, Iqbal Gondal, Venki Balasubrammanian, “Blockchain Leveraged Decentralized IoT eHealth Framework” Journal of Internet of Things Cyber Physical Human Systems, ELSEVIER publisher, Impact factor:1.764, 2020
• Md. Ashraf Uddin, Andrew Stranieri, Iqbal Gondal, Venki Balasubrammanian, “A Lightweight Blockchain Based Framework for Underwater IoT” Electronics Journal, Impact factor:1.764, 2020
• Mahbub E Khoda, Tasadduq Imam, Joarder Kamruzzaman, Iqbal Gondal and Ashfaqur Rahman “Robust Malware Defense in Industrial IoT Applications using Machine Learning with Selective Adversarial Samples” IEEE Transactions on Industry Applications, I.F. 3.347, 2020
• Sona Taheri, Iqbal Gondal, Adil Bagirov, Simon Brown, “Cyber-attack Triage using Incremental Clustering for Intrusion Detection Systems” International Journal of Information Security, I.F. 1.822, 2020
• Khoda, M. E., Kamruzzaman, J., Gondal, I., Imam, T., & Rahman, A. (2020, October). Mobile malware detection with imbalanced data using a novel synthetic oversampling strategy and deep learning. In 2020 16th international conference on wireless and mobile computing, networking and communications (WiMob) (pp. 1-6). IEEE.

2019

• Black P., Gondal I., Vamplew P., and Lakhotia A., Evolved Similarity Techniques in Malware Analysis (Trustcom 2019)
• Ansam Khraisat; Iqbal Gondal; Peter Vamplew; Joarder Kamruzzaman, Ammar Alazab, “A novel Ensemble of Hybrid Intrusion Detection System for Detecting Internet of Things Attacks, Journal Electronics (ISSN 2079-9292; CODEN: ELECGJ), 2019, I.F. 1.764
• Ansam Khraisat; Iqbal Gondal; Peter Vamplew; Joarder Kamruzzaman, “Survey of Intrusion Detection Systems: Techniques, Datasets and Challenges” Cybersecurity Journal, Springer 2019 IF. 1.822
• Khoda, M. E., Imam, T., Kamruzzaman, J., Gondal, I., & Rahman, A. (2019). Robust malware defense in industrial IoT applications using machine learning with selective adversarial samples. IEEE Transactions on Industry Applications, 56(4), 4415-4424.
• Khoda, M., Imam, T., Kamruzzaman, J., Gondal, I., & Rahman, A. (2019, August). Selective adversarial learning for mobile malware. In 2019 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) (pp. 272-279). IEEE.
• Khoda, M. E., Kamruzzaman, J., Gondal, I., Imam, T., & Rahman, A. (2019, February). Mobile malware detection: An analysis of deep learning model. In 2019 IEEE International Conference on Industrial Technology (ICIT) (pp. 1161-1166). IEEE.

2018

• Black P., Gondal I., and Layton R., A Survey of Similarities in Banking Malware Behaviours. (Computers and Security Journal, 2018).
• Md. Ashraf Uddin, Andrew Stranieri, Iqbal Gondal, Venki Balasubrammanian, “Continuous Patient Monitoring With a Patient Centric Agent: A Block Architecture” IEEE Access Journal, Impact factor:3.6, 2018
• Uddin, M. A., Stranieri, A., Gondal, I., & Balasubramanian, V. (2018). Continuous patient monitoring with a patient centric agent: A block architecture. IEEE Access, 6, 32700-32726.

2016

• Black P., and Opacki J., Anti-analysis trends in banking malware, Malicious and Unwanted Software (MALWARE), 2016 11th International Conference on. IEEE.
• Lakhotia A., and Black P., Mining Malware Secrets, In Malicious and Unwanted Software (MALWARE), 2016 11th International Conference on. IEEE.
• Khoda, M. E., Razzaque, M. A., Almogren, A., Hassan, M. M., Alamri, A., & Alelaiwi, A. (2016). Efficient computation offloading decision in mobile cloud computing over 5G network. Mobile Networks and Applications, 21(5), 777-792.

2014

• Black, P., and Layton R., Be careful who you trust: Issues with the public key infrastructure, Cybercrime and Trustworthy Computing Conference (CTC), 2014, IEEE.