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ICARIS
2005
Springer
13 years 10 months ago
A Comparative Study of Real-Valued Negative Selection to Statistical Anomaly Detection Techniques
The (randomized) real-valued negative selection algorithm is an anomaly detection approach, inspired by the negative selection immune system principle. The algorithm was proposed t...
Thomas Stibor, Jonathan Timmis, Claudia Eckert
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
13 years 10 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...
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
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 5 months ago
Discriminating self from non-self with finite mixtures of multivariate Bernoulli distributions
Affinity functions are the core components in negative selection to discriminate self from non-self. It has been shown that affinity functions such as the r-contiguous distance an...
Thomas Stibor
GECCO
2003
Springer
113views Optimization» more  GECCO 2003»
13 years 10 months ago
The Effect of Binary Matching Rules in Negative Selection
Negative selection algorithm is one of the most widely used techniques in the field of artificial immune systems. It is primarily used to detect changes in data/behavior patterns...
Fabio A. González, Dipankar Dasgupta, Jonat...