TY - GEN
T1 - The use of mobile agents in tracing an intruder in a local area network
AU - Asaka, Midori
AU - Onabuta, T.
AU - Inoue, T.
AU - Goto, Shigeki
PY - 2000
Y1 - 2000
N2 - We are developing an intrusion detection agent system called IDA. Not only can the IDA detect an intrusion, it can also trace the route of the intrusion in a local area network. It is very important for administrators to know where an intruder is coming from and which machines the intruder hopped and compromised in the LAN because the administrators must restore the compromised systems, especially the system attacked first, in order to help prevent intrusions again. When a mark is detected indicating that an intruder might leave, the IDA starts collecting information related to the mark as it traces the candidate. The system analyzes the information and decides whether an intrusion has occurred. In the IDA, mobile agents collect information from the target systems across the network and trace the intruder. The mobile agents collect information only related to the intrusion. Therefore, the IDA can reduce analyzing overhead and network bandwidth loss.
AB - We are developing an intrusion detection agent system called IDA. Not only can the IDA detect an intrusion, it can also trace the route of the intrusion in a local area network. It is very important for administrators to know where an intruder is coming from and which machines the intruder hopped and compromised in the LAN because the administrators must restore the compromised systems, especially the system attacked first, in order to help prevent intrusions again. When a mark is detected indicating that an intruder might leave, the IDA starts collecting information related to the mark as it traces the candidate. The system analyzes the information and decides whether an intrusion has occurred. In the IDA, mobile agents collect information from the target systems across the network and trace the intruder. The mobile agents collect information only related to the intrusion. Therefore, the IDA can reduce analyzing overhead and network bandwidth loss.
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M3 - Conference contribution
AN - SCOPUS:84867752517
SN - 3540679251
SN - 9783540679257
VL - 1886 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 373
EP - 382
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 6th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2000
Y2 - 28 August 2000 through 1 September 2000
ER -