Artificial immune systems for the detection of credit card fraud: an architecture, prototype and preliminary results Nicholas Wong,* Pradeep Ray,* Greg Stephens* & Lundy Lewis † *C/- School of Information Systems, Technology and Management, University of New South Wales, Sydney, New South Wales Australia, email: p.ray@unsw.edu.au, and † Department of Computer Information Technology, Southern New Hampshire University, Manchester, New Hampshire, USA, email: l.lewis@snhu.edu Abstract. Some biological phenomena offer clues to solving real-life, complex problems. Researchers have been studying techniques such as neural networks and genetic algorithms for computational intelligence and their applications to such complex problems. The problem of security management is one of the major concerns in the development of eBusiness services and networks. Recent inci- dents have shown that the perpetrators of cybercrimes are using increasingly sophisticated methods. Hence, it is necessary to investigate non-traditional mechanisms, such as biological techniques, to manage the security of evolving eBusiness networks and services. Towards this end, this paper investigates the use of an Artificial Immune System (AIS). The AIS emulates the mechanism of human immune systems that save human bodies from complex natural biological attacks. The paper discusses the use of AIS on one aspect of security manage- ment, viz. the detection of credit card fraud. The solution is illustrated with a case study on the management of frauds in credit card transactions, although this technique may be used in a range of security management applications in eBusiness. Keywords: artificial immune systems, security management, credit card fraud detection, eBusiness INTRODUCTION A wide range of security problems beset e-commerce. For example, a major problem faced by e-commerce retailers is the problem of online credit card payment fraud. The following statistics highlight the prominence and cost of this problem: The work reported in this paper was partially supported by the Australian Research Council Discovery Grant (DP0451650) Distributed Autonomic Management (DAM): A New Paradigm for Integrated Network Management. doi:10.1111/j.1365-2575.2011.00369.x Info Systems J (2012) 22, 53–76 53 © 2011 Blackwell Publishing Ltd