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This paper presents a potential solution to the intrusion detection problem in computer security. It uses a combination of work in the fields of Artificial Life and computer security. It shows how an intrusion detection system can be implemented using autonomous agents, and how these agents can be built using Genetic Programming. It also shows how Automatically Defined Functions (ADFs) can be used to evolve genetic programs that contain multiple data types and yet retain type-safety. Future work arising from this is also discussed. Introduction Genetic Programming (GP) has been used to solve many problems that occur in the real world. Koza's book (Koza 1992) has numerous examples of using GP techniques to solve problems in a variety of fields. This paper presents a new application of genetic programming to solve a problem in the field of computer security. This application will exploit the learning power of GP. In the course of designing a solution to the problem, a novel use for Auto...

We grow increasingly dependent on the appropriate operation of computer-based systems. One aspect of such systems is security. As systems become more complex current means of analysis will probably prove ineffective. In the safety domain a variety of analysis techniques has emerged over many years. These have proved surprisingly effective. Since the safety and security domains share many similarities, various authors have suggested that safety techniques might usefully find application in security. This report takes one such technique, HAZOPs, and applies it to one widely used informal design component – UML’s use cases.

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