Professor Kim Kwang-Jo, publication on network intrusion detection using artificial intelligence in English

Kim Kwang, professor of KAIST (President: Sang Chul Shin) Graduate School of Computing and Information Security Graduate School, along with Muhamad Erza Aminanto and Dr. Harry Chandra Tanuwidjaja, Ph.D. students from Indonesia, wrote an English book called “Network Intrusion Detection using Deep Learning : A Feature Learning Approach” (in the aspected of network intrusion detection using features of deep learning) which supported by IITP’s project on “Communication Technology Research using Bio-inspired Algorithm” from April 2018 to February 2018. He has published this in one of the cyber security systems and networking series at Springer, a prominent publisher in Germany.

This book introduces various methods of intrusion detection system using deep learning, which is artificial intelligence technique and widely used in computer vision, natural language processing, image processing, etc., and described an intrusion detection technique which extracts and learns the features of intrusion traffic with very high scan rate (99.918%) and low false positives (0.012%) compared to existing skills. Annexes include technical trends on artificial intelligence techniques for detecting malicious codes.
This book will serve as a good guide for undergraduate and graduate students, R & D personnel in providing practical knowledge of establishing cyber security systems regarding graft artificial intelligence onto cyber security.