JICCE (한국정보통신학회)
Current Result Document :
| 한글제목(Korean Title) |
Design of Hybrid Network Probe Intrusion Detector using FCM |
| 영문제목(English Title) |
Design of Hybrid Network Probe Intrusion Detector using FCM |
| 저자(Author) |
Chang-Su Kim
Se-Yul Lee
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| 원문수록처(Citation) |
VOL 07 NO. 01 PP. 0007 ~ 0012 (2009. 03) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The advanced computer network and Internet technology enables connectivity of computers through an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We proposed a network based hybrid Probe Intrusion Detection model using Fuzzy cognitive maps (PIDuF) that detects intrusion by DoS (DDoS and PDoS) attack detection using packet analysis. A DoS attack typically appears as a probe and SYN flooding attack. SYN flooding using FCM model captures and analyzes packet information to detect SYN flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance evaluation, the “IDS Evaluation Data Set” created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.064% and the max-average false negative rate of 2.936%. The true positive error rate of the PIDuF is similar to that of Bernhard’s true positive error rate. |
| 키워드(Keyword) |
Fuzzy Cognitive Maps
Probe Detection
SYN Flooding
DDoS and PDoS
Intrusion Detection
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| 파일첨부 |
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