• The KIPS Transactions:PartC
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• v.12C no.1 s.97
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• pp.45-52
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• 2005

A damage scale of information property has been increasing rapidly by various illegal actions of information systems, which result from dysfunction of a knowledge society. Reinforcement in criminal investigation requests of network security has accelerated research and development of Intrusion Detection Systems(IDSs), which report intrusion-detection about these illegal actions. Due to limited designs of early IDSs, it is hard for the IDSs to cope with tricks to go around IDS as well as false-positive and false-negative trials in various network environments. In this paper, we showed that this kind of problems can be solved by using a Virtual Protocol Stack(VPS) that possesses automatic learning ability through an optimum-adaptive mobile code. Therefore, the enhanced IDS adapts dynamically to various network environments in consideration of monitored and self-learned network status. Moreover, it is shown that Insertion/Evasion attacks can be actively detected. Finally, we discussed that this method can be expanded to an intrusion detection technique that possesses adaptability in the various mixed network environments.