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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

The Rule Based Intrusion Detection and Prevention Model for Biometric System

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Author Maithili Arjunwadkar, R.V. Kulkarni
ISSN 2079-8407
On Pages 117-120
Volume No. 1
Issue No. 2
Issue Date October 1, 2010
Publishing Date October 1, 2010
Keywords Security, biometric process, attacks, intrusion detection, prevention, expert system.


Abstract

Modern biometric systems claim to provide alternative solution to traditional authentication processes. Even though there are various advantages of biometric process, it is vulnerable to attacks which can decline it’s security. The intrusion detection is an essential supplement of traditional security system. This security system needs the robust automated auditing, intelligent reporting mechanism and robust prevention techniques. We suggest rule based intelligent intrusion detection and prevention model for biometric system. This model contains a scheduler to prepare a schedule to check different logs for possible intrusions, detectors to detect normal or abnormal activity. If activity is normal then alarming and reporting has been executed. If abnormal activity is found the rule engine fires the rule to detect intrusion point and type of intrusion. The model also contains an expert system to detect source of intrusion and suggest best possible prevention technique and suitable controls for different intrusions. This model is also used for security audit as well as alarming and reporting mechanisms. The malicious activity database is stored for future intrusion detection. To detect source tracking backward chaining approach is used. The rules are defined and stored in the Rule engine of the system.


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