Classification and detection of computer intrusions
Classification and detection of computer intrusions
Principles of a computer immune system
NSPW '97 Proceedings of the 1997 workshop on New security paradigms
Behavior-based intrusion detection in mobile phone systems
Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
An Architecture for Intrusion Detection Using Autonomous Agents
ACSAC '98 Proceedings of the 14th Annual Computer Security Applications Conference
An artificial immune based intrusion detection model for computer and telecommunication systems
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
VMFence: a customized intrusion prevention system in distributed virtual computing environment
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Intelligent agent based artificial immune system for computer security--a review
Artificial Intelligence Review
Lightweight and distributed attack detection scheme in mobile ad hoc networks
Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia
An immune mobile agent based grid intrusion detection model
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Immunity and mobile agent based intrusion detection for grid
PRIMA'06 Proceedings of the 9th Pacific Rim international conference on Agent Computing and Multi-Agent Systems
Immunity and mobile agent based grid intrusion detection
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
A VMM-based intrusion prevention system in cloud computing environment
The Journal of Supercomputing
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Agent Based Models are the natural extension of the Ising or Cellular Automata-like models which have been used in the past decades to simulate various physical phenomena. By taking advantages of the main features of such models, coupled with nature based models such as artificial immune systems we present a novel artificial immune and agent based intrusion detection model for large computer networks. Our solution is based upon several security levels, event based model, and a simple computational abstraction where an anomaly detection technique is designed to monitor the users' registrations to the operational targeted system, e.g., UNIX-like implementation. In our model, the events' generation model is processed using the Unix Syslog-ng tool, the events' analysis using the Logcheck tool, while the activities of the users and the execution of the both reactive and pro-active events' activities are implemented within an artificial immune and mobile agent based infrastructure. We have implemented and designed our model to differentiate among attacks, security violations, and several other security levels. In this paper we present our model, and show how mobile agent and artificial immune paradigms can be used to design efficient intrusion detection systems. wealso discuss the validation of our model followed by a set of experiments we have carried out to evaluate the performance of our model using realistic case studies.