Shajina Anand

As cyber threats become more advanced, traditional security models struggle to keep up with protecting modern networks. The Zero Trust framework, based on the idea of verifying and authorizing access at every step, regardless of user location or device, offers a solid solution. Adding Artificial Intelligence to this approach makes it even more effective by enabling smarter threat detection, continuous monitoring, and adaptive security measures.

This talk looks at how AI improves zero-trust networks, focusing on AI algorithms like Long Short-Term Memory (LSTM) that can track network behavior over time to spot unusual activity and potential threats. AI also helps prioritize which threats need the most attention using risk scoring, making it easier to handle the most serious risks first.

With AI-powered monitoring, even small security issues can be detected and addressed in real time, improving response times and overall protection. Combining AI with Zero Trust creates a more flexible and robust security system, ready to tackle the ever-changing challenges in cybersecurity.

Biography:

Dr. Shajina Anand is an Assistant Professor of Cybersecurity and Computer Science at Seton Hall University. She is the founding director of the Cybersecurity Lab, which serves as a research and teaching facility for Computer Science students enrolled in her courses. At Seton Hall University, she has developed advanced courses covering various aspects of Cybersecurity, including network security and IoT security. Her research spans areas such as vulnerability analysis, risk assessment, social engineering, and the detection and mitigation of cybersecurity attacks using Machine Learning/AI. She holds a Ph.D. in Computer Science from Anna University, India.