Rate My Professor Erwin Adi

Adi has an extensive publication record in prestigious journals, showcasing his expertise across various cybersecurity domains. Notable works include 'Artificial Intelligence for Cybersecurity: Offensive Tactics, Mitigation Techniques and Future Directions' (2022, Applied Cybersecurity & Internet Governance, with Z. Baig and S. Zeadally), 'AI-based audit of fuzzy front end innovation using ISO56002' (2021, Managerial Auditing Journal, with R. Khan and O. Hussain), 'Machine learning and data analytics for the IoT' (2020, Neural Computing and Applications, with A. Anwar, Z. Baig, and S. Zeadally), 'Harnessing artificial intelligence capabilities to improve cybersecurity' (2020, IEEE Access, with S. Zeadally, Z. Baig, and I.A. Khan), 'A New Threat Intelligence Scheme for Safeguarding Industry 4.0 Systems' (2018, IEEE Access, with N. Moustafa, B. Turnbull, and J. Hu), 'Stealthy Denial of Service (DoS) attack modelling and detection for HTTP/2 services' (2017, Journal of Network and Computer Applications, with Z. Baig and P. Hingston), 'Distributed denial-of-service attacks against HTTP/2 services' (2016, Cluster Computing, with Z. Baig, P. Hingston, and C.P. Lam), and 'Securing mobile healthcare data: A smart card based cancelable Finger-Vein Bio-Cryptosystem' (2018, IEEE Access, with W. Yang et al.). These publications highlight his advancements in AI-enhanced security protocols, anomaly detection, and protocol-specific attack mitigation, influencing academic discourse on proactive cybersecurity measures.