A Real-Time Intrusion Detection System using Data Mining Technique
Fang-Yie Leu, Kai-Wei Hu
Presently, most computers authenticate user ID and password
before users can login these systems. However, danger soon
comes if the two items are known to hackers. In this paper, we
propose a system, named Intrusion Detection and Identification
System (IDIS), which builds a profile for each user in an intranet
to keep track his/her usage habits as forensic features with which
IDIS can identify who the underlying user in the intranet is. Our
experimental results show that the recognition accuracy of
students of computer science department is up to 98.99%. Full Text
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