Practical Traffic-space Adversarial Attacks on Learning-based NIDSs

15 May 2020Dongqi HanZhiliang WangYing ZhongWenqi ChenJiahai YangShuqiang LuXingang ShiXia Yin

Machine learning (ML) techniques have been increasingly used in anomaly-based network intrusion detection systems (NIDS) to detect unknown attacks. However, ML has shown to be extremely vulnerable to adversarial attacks, aggravating the potential risk of evasion attacks against learning-based NIDSs... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.