Modern machine learning techniques provide robust approaches for data-driven modeling and critical information extraction, while human experts hold the advantage of possessing hig...
The massive amount of alarm data generated from intrusion detection systems is cumbersome for network system administrators to analyze. Often, important details are overlooked and...
Kulsoom Abdullah, Christopher P. Lee, Gregory J. C...
Attackers often try to evade an intrusion detection system (IDS) when launching their attacks. There have been several published studies in evasion attacks, some with available to...
Traffic anomalies and attacks are commonplace in today’s networks and identifying them rapidly and accurately is critical for large network operators. For a statistical intrusi...
Pin Ren, Yan Gao, Zhichun Li, Yan Chen, Benjamin W...
— In this paper, we propose an endpoint-based joint network-host anomaly detection technique to detect selfpropagating malicious codes. Our proposed technique is based on the obs...