At the Information-technology Promotion Agency (IPA), we have been developing a network intrusion detection system called IDA (Intrusion Detection Agent system). IDA system has two distinctive features that most conventional intrusion detection systems lack. First, it has a mechanism for tracing the origin of a break-in by means of mobile agents. Second, it has a new and efficient method of detecting intrusions: rather than continuously monitoring the user's activities, it watches for an event that meets the criteria of an MLSI (Mark Left by Suspected Intruders) and may relate to an intrusion. By this method, IDA described herein can reduce the processing overhead of systems and networks. At present, IDA can detect local attacks that are initiated against a machine to which the attacker already has access and he or she attempts to exceed his or her authority. This paper mainly describes how IDA detects local attacks and traces intrusions.

Many methods have been proposed to detect intrusions; for example, the pattern matching method on known intrusion patterns and the statistical approach to detecting deviation from normal activities. We investigated a new method for detecting intrusions based on the number of system calls during a user's network activity on a host machine. This method attempts to separate intrusions from normal activities by using discriminant analysis, a kind of multivariate analysis. We can detect intrusions by analyzing only 11 system calls occurring on a host machine by discriminant analysis with the Mahalanobis' distance, and can also tell whether an unknown sample is an intrusion. Our approach is a lightweight intrusion detection method, given that it requires only 11 system calls for analysis. Moreover, our approach does not require user profiles or a user activity database in order to detect intrusions. This paper explains our new method for the separation of intrusions and normal behavior by discriminant analysis, and describes the classification method by which to identify an unknown behavior.

The number of computer break-ins from the outside of an organization has increased with the rapid growth of the Internet. Since many intruders from the outside of an organization employ stepping stones, it is difficult to trace back where the real origin of the attack is. Some research projects have proposed tracing methods for DoS attacks and detecting method of stepping stones. It is still difficult to locate the origin of an attack that uses stepping stones. We have developed IDA (Intrusion Detection Agent system), which has an intrusion tracing mechanism in a LAN environment. In this paper, we improve the tracing mechanism so that it can trace back stepping stones attack in the Internet. In our method, the information about tracing stepping stone is collected from hosts in a LAN effectively, and the information is made available at the public information server. A pursuer of stepping stone attack can trace back the intrusion based on the information available at the public information server on an intrusion route.