An artificial immune based intrusion detection model for computer and telecommunication systems

Abstract

Recent years have seen a growing interest in computational methods based upon natural phenomena with biologically inspired techniques, such as cellular automata, immune human systems, neural networks, DNA and molecular computing. Some of these techniques are classified under the realm of a general paradigm, called bio-computing. In this paper, we propose a security system for fraud detection of intruders and improper use of both computer system and mobile telecommunication operations. Our technique is based upon data analysis inspired by the natural immune human system. We show how immune metaphors can be used efficiently to tackle this challenging problem. We also describe how our scheme extracts salient features of the immune human system and maps them within a software package designed to identify security violations of a computer system and unusual activities according to the usage log files. Our results indicate that our system shows a significant size reduction of the logs file (i.e., registration of each log activity), and thereby the size of the report maintained by the computer system manager. This might help the system manager to monitor and observe unusual activities on the machine hosts more efficiently, as they happen, and can act accordingly before it is too late. Last but not least, we propose an intrusion and fraud detection model based upon immune human analogy for mobile phone operations. We discuss our model and present its specification using the Z Language.