Se Chung Pang , Yang Woo Kim , Yoon Hee Kim , Phil Woo Lee

The KIPS Transactions:PartC, Vol. 12, No. 1, pp. 45-52, Feb. 2005
10.3745/KIPSTC.2005.12.1.45,   PDF Download:

Abstract

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 limites designs of early IDSs, it is hard for the IDSs to cope with tricks to fo 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.

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