Application of AI in Cyber Security
About the speaker
Dr. Mohit Sewak is an AI researcher, TED speaker, and author of best-selling books on AI. With over two dozen AI patents, his inventive spirit shines. He is a researcher and author of several peer-reviewed scientific research papers in AI & ML and distinguished industry-leader in AI product innovation, development, and engineering. Dr. Mohit is a leader in AI product development, creating solutions for Retail, IoT, BFSI, and Cyber Security. His work in Deep-Reinforced Agent, Computer-Vision, and Deep-NLP is transforming industries.
Synopsis
In this session, Dr. Mohit Sewak delves into the intricate realm of the Cybersecurity Defense Landscape, shedding light on the pressing issue of Malware Detection, which is bad software. He explains how regular Machine Learning and fancy techniques like Deep Learning work to identify this bad software. He explains the complexities of Deep Learning, DNN, Auto Encoders, LSTM, Value DRL, Policy DRL, and Deep Clustering, which are just different tools.
Drawing distinctions among different generations of malware, Dr. Mohit delves into the Evolution of Malware Detection, highlighting key research work in Deep Learning. Engaging insights cover non-recurrent deep learning methodologies that hold potential in the fight against malicious software. Get ready to gain a comprehensive understanding of the world of Cybersecurity, as Dr. Mohit navigates through innovative approaches and cutting-edge techniques in malware detection.
