By : Anas Assiri

Introduction fraud detection Immune systemArtificial immune system (AIS)AISFDClonal selection

The immune system is highly complicated detecting and eliminating infections similar problem: credit card fraud detection

Artificial immune system (AIS) Immunological computation is an area of biologically inspired

computation.

AIS and other soft computing paradigms: ANN (artificial neural network) EA (evolutionary algorithms) FS (fuzzy system) PR (probabilistic reasoning).

AISFD is a system based on AIS and case-based reasoning (CBR).

Artificial Immune system is inspired from biological immune system.

Tow main algorithms : Negative selection Clonal selection

Negative selection The purpose of negative selection is to

provide self-tolerance to T-cells. It detects unknown antigens, without reacting with the self cells.

Clonal selection The clonal selection principle describes the

basic features of an immune response to an antigenic stimulus. It can make sure only the cells that can recognize the antigen can proliferate.

Gene library evolution Gene library evolution learns knowledge of

currently existing antigens.

library of past cases rather than being encoded in classical

rules Each case typically contains : a description of the problem and a solution and or the outcome

The knowledge and reasoning process used by an expert to solve the problem is not recorded, but is implicit in the solution

To solve a current problem:

Case library initialization (normal transactions and fraud transactions case) With supervised classification

Antibody Gene (detectors.)library Initialization Random or genetic algorithms

Negative selection of detectorsClonal selection of detectors

Fraud detection When a new transaction is submitted for

frauddetection, the fraud detection function is

activated. The affinity between the antibodies (detectors) in the gene library and the new antigens is calculated. If the affinity threshold set by the system is exceeded, the AISFD system sends out a fraud alert.

DiversificationOnline incremental learningSelf-adaptationDistributionFast responseMulti-level classification

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