Techniques are described herein for clustering network hosts based on their network behavior to create groups of hosts that behave similarly. An anomaly detection model trained on a single group of network hosts is more robust to fluctuations of the behavior of individual hosts when compared to the per host models. When comparing to the group all models that are trained using the behavior of all network hosts, finer anomalies (e.g., stealthy data exfiltration) that would otherwise be hidden may be detected by modelling diversely behaving network hosts
The ability to detect unexpected events in large networks can be a significant benefit to daily netw...
Abstract: New datamining techniques are developed for generating frequent episode rules of traffic e...
Nowadays, organization networks are facing an increased number of different attacks and existing int...
Current network access control systems can contain unpredictable interactions between multiple devic...
Anomaly detection is based on profiles that represent normal behavior of users, hosts or networks an...
As information systems become increasingly complex and pervasive, they become inextricably intertwin...
In IP networks, an anomaly detection system identifies attacks, device failures or other unknown pro...
Abstract Much of the intrusion detection research focuses on signature (misuse) detection, where mod...
Network anomaly detection solutions are being used as defense against several attacks, especially th...
Network anomaly detection is an effective way to detect intrusions which defends our computer system...
International audienceNetwork anomalies and attacks represent a serious challenge to ISPs, who need ...
Information systems and their services (referred to as cyberspace) are ubiquitous and touch all aspe...
Most existing network intrusion detection systems use signature-based methods which depend on labele...
Observing network traffic flow for anomalies is a common method in Intrusion Detection. More effort ...
Intrusion detection systems (IDS) play a critical role in network security by monitoring systems and...
The ability to detect unexpected events in large networks can be a significant benefit to daily netw...
Abstract: New datamining techniques are developed for generating frequent episode rules of traffic e...
Nowadays, organization networks are facing an increased number of different attacks and existing int...
Current network access control systems can contain unpredictable interactions between multiple devic...
Anomaly detection is based on profiles that represent normal behavior of users, hosts or networks an...
As information systems become increasingly complex and pervasive, they become inextricably intertwin...
In IP networks, an anomaly detection system identifies attacks, device failures or other unknown pro...
Abstract Much of the intrusion detection research focuses on signature (misuse) detection, where mod...
Network anomaly detection solutions are being used as defense against several attacks, especially th...
Network anomaly detection is an effective way to detect intrusions which defends our computer system...
International audienceNetwork anomalies and attacks represent a serious challenge to ISPs, who need ...
Information systems and their services (referred to as cyberspace) are ubiquitous and touch all aspe...
Most existing network intrusion detection systems use signature-based methods which depend on labele...
Observing network traffic flow for anomalies is a common method in Intrusion Detection. More effort ...
Intrusion detection systems (IDS) play a critical role in network security by monitoring systems and...
The ability to detect unexpected events in large networks can be a significant benefit to daily netw...
Abstract: New datamining techniques are developed for generating frequent episode rules of traffic e...
Nowadays, organization networks are facing an increased number of different attacks and existing int...