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INFOCOM
2011
IEEE
12 years 8 months ago
A comparative study of two network-based anomaly detection methods
—Modern networks are complex and hence, network operators often rely on automation to assist in assuring the security, availability, and performance of these networks. At the cor...
Kaustubh Nyalkalkar, Sushant Sinha, Michael Bailey...
CORR
2010
Springer
167views Education» more  CORR 2010»
13 years 4 months ago
The DCA:SOMe Comparison A comparative study between two biologically-inspired algorithms
The Dendritic Cell Algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation ...
Julie Greensmith, Jan Feyereisl, Uwe Aickelin
RAID
2004
Springer
13 years 10 months ago
Anomaly Detection Using Layered Networks Based on Eigen Co-occurrence Matrix
Anomaly detection is a promising approach to detecting intruders masquerading as valid users (called masqueraders). It creates a user profile and labels any behavior that deviates...
Mizuki Oka, Yoshihiro Oyama, Hirotake Abe, Kazuhik...
IMC
2005
ACM
13 years 10 months ago
Combining Filtering and Statistical Methods for Anomaly Detection
In this work we develop an approach for anomaly detection for large scale networks such as that of an enterprize or an ISP. The traffic patterns we focus on for analysis are that...
Augustin Soule, Kavé Salamatian, Nina Taft
ICDM
2009
IEEE
150views Data Mining» more  ICDM 2009»
13 years 2 months ago
Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...
Xiao Yu, Lu An Tang, Jiawei Han