Program anomaly detection analyzes normal program behaviors and discovers aberrant executions caused by attacks, misconfigurations, program bugs, and unusual usage patterns. The merit of program anomaly detection is its independence from attack signatures, which enables proactive defense against new and unknown attacks. In this paper, we formalize the general program anomaly detection problem a...

Anomaly detection is a challenging problem that has been researched within a variety of application domains such as image processing, fault isolation, fraud detection, and network intrusion detection. In network intrusion detection, anomaly based techniques are particularly attractive because of their ability to identify previously unknown attacks without the need to be programmed with the spec...

a r t i c l e i n f o The paper presents an implementable method of anomaly detection for satellite power system. Specifically, a data-driven anomaly detection method for sensor data integrated Kernel Principal Component Analysis (KPCA) and association rule mining is demonstrated. Establishing associated rules among sensor monitoring data sets, this approach analyses the structure of measure sp...

Recent studies estimate that peer-to-peer (p2p) traffic comprises 40-70% of today’s Internet traffic [1]. Surprisingly, the impact of p2p traffic on anomaly detection has not been investigated. In this paper, we collect and use a labeled dataset containing diverse network anomalies (portscans, TCP floods, UDP floods, at varying rates) and p2p traffic (encrypted and unencrypted with BitTorrent, ...

We present a direct field theoretical calculation of the consistent gauge anomaly in the superfield formalism, on the basis of a definition of the effective action through the covariant gauge current. The scheme is conceptually and technically simple and the gauge covariance in intermediate steps reduces calculational labors considerably. The resultant superfield anomaly, being proportional to ...