CDIS: Towards a Computer Immune System for Detecting Network Intrusions
RAID '00 Proceedings of the 4th International Symposium on Recent Advances in Intrusion Detection
A Synthetic Fraud Data Generation Methodology
ICICS '02 Proceedings of the 4th International Conference on Information and Communications Security
Architecture for an Artificial Immune System
Evolutionary Computation
Information security standards for e-businesses
ICCS '02 Proceedings of the The 8th International Conference on Communication Systems - Volume 02
MOBAIS: A Bayesian Artificial Immune System for Multi-Objective Optimization
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Viral System to Solve Optimization Problems: An Immune-Inspired Computational Intelligence Approach
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Credit Card Fraud Detection with Artificial Immune System
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Conserved Self Pattern Recognition Algorithm
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Using identity credential usage logs to detect anomalous service accesses
Proceedings of the 5th ACM workshop on Digital identity management
Artificial Dendritic Cells Algorithm for Online Break-In Fraud Detection
DESE '09 Proceedings of the 2009 Second International Conference on Developments in eSystems Engineering
The application of a dendritic cell algorithm to a robotic classifier
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
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Fraud is one of the largest growing problems experienced by many organizations as well as affecting the general public. Over the past decade the use of global communications and the Internet for conducting business has increased in popularity, which has been facing the fraud threat. This paper proposes an immune inspired adaptive online fraud detection system to counter this threat. This proposed system has two layers: the innate layer that implements the idea of Dendritic Cell Analogy (DCA), and the adaptive layer that implements the Dynamic Clonal Selection Algorithm (DCSA) and the Receptor Density Algorithm (RDA). The experimental results demonstrate that our proposed hybrid approach combining innate and adaptive layers of immune system achieves the highest detection rate and the lowest false alarm rate compared with the DCA, DCSA, and RDA algorithms for Video-on-Demand system.