Our research in Cybersecurity is centered on understanding how malicious entities might exploit AI systems for personal gain or to sow anarchy. This area of study is critical as AI technologies become increasingly integrated into various aspects of daily life and critical infrastructure. By identifying potential vulnerabilities and the methods by which bad actors could influence or corrupt AI models, we aim to develop a comprehensive understanding of the threats faced by these systems. This includes investigating data poisoning, model stealing, and adversarial attacks that can subtly alter AI behavior in detrimental ways.
To counter these threats, our research also focuses on developing robust defensive strategies that enhance the security of AI systems. This involves creating more resilient machine learning models that can detect and resist manipulations, as well as implementing rigorous testing scenarios that simulate potential attack vectors. By advancing these protective measures, we strive to not only protect AI systems from malicious attacks but also to foster a safer deployment of AI technologies across all sectors. This proactive approach ensures that the benefits of AI can be enjoyed without the looming threat of exploitation by bad actors.