v-detector: a negative selection algorithm zhou ji, advised by prof. dasgupta computer science...
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V-Detector: A Negative Selection AlgorithmZhou Ji, advised by Prof. Dasgupta
Computer Science Research Day The University of MemphisMarch 25, 2005
Background Immune system
is a group of cells and organs that work together to fight infections in our bodies.
Background AIS (Artificial Immune Systems) are not
just intrusion detection and defense Immune system’s computational
capability Learning Memory Recognition Feature extraction Distributed process Adaptation Self/nonself discrimination Prediction ……
Background
Different models of Artificial Immune Systems Negative selection algorithms Immune network model Clonal selection Gene library
Background
Negative Selection Algorithms In natural immune system: T-cells develop in
thymus Random generation + aimed elimination Represent target concept by negative space Training only with self samples – “one class”
learning
Algorithm
basic idea
Algorithm
V-detector
Algorithm
V-detector’s features Simple generation strategy and
detector scheme - extensibility Variable sized detectors Coverage estimate Boundary-aware
Implementation
Multiple dimensional, Real-valued representation
Control parameters Self threshold Target coverage Significant level (for hypothesis
testing) Boundary-aware vs. point-wise
Implementation
User interface
Experiments
Summary
A new negative selection algorithm has been developed.
Important unique features. Challenges: evaluate the
detectors and categorize the anomaly.
Bibliography Ji & Dasgupta, Augmented Negative
Selection Algorithm with Variable-Coverage Detectors, CEC 2004
Ji & Dasgupta, Real-valued Negative Selection Algorithm with Variable-Sized Detectors, GECCO 2004
Ji & Dasgupta, Estimating the Detector Coverage in a Negative Selection Algorithm, GECCO 2005