Baiting AI: Deceptive Adversary against AI-Protected Industrial Infrastructures

This paper explores a new cyber-attack vector targeting Industrial Control Systems ICS, particularly focusing on water treatment facilities. Developing a new multi-agent Deep Reinforcement Learning DRL approach, adversaries craft stealthy, strategically timed, wear-out attacks designed to subtly...

Cybercrime and Computer Forensics in Epoch of Artificial Intelligence in India

The integration of generative Artificial Intelligence into the digital ecosystem necessitates a critical re-evaluation of Indian criminal jurisprudence regarding computational forensics integrity. While algorithmic efficiency enhances evidence extraction, a research gap exists regarding the Digit...

Towards Secure MLOps: Surveying Attacks, Mitigation Strategies, and Research Challenges

The rapid adoption of machine learning ML technologies has driven organizations across diverse sectors to seek efficient and reliable methods to accelerate model development-to-deployment. Machine Learning Operations MLOps has emerged as an integrative approach addressing these requirements by...

AIs Discovering Vulnerabilities

I've been writing about the possibility of AIs automatically discovering code vulnerabilities since at least 2018. This is an ongoing area of research: AIs doing source code scanning, AIs finding zero-days in the wild, and everything in between. The AIs aren't very good at it yet, but they're...

Breaking the Bank: Weakness in Financial AI Applications

Currently, threat actors possess limited access to the technology required to conduct disruptive operations against financial artificial intelligence AI systems and the risk of this targeting type remains low. However, there is a high risk of threat actors leveraging AI as part of disinformation...