首页    期刊浏览 2025年02月22日 星期六
登录注册

文章基本信息

  • 标题:The Rule Based Intrusion Detection and Prevention Model for Biometric System
  • 本地全文:下载
  • 作者:Maithili Arjunwadkar ; R.V. Kulkarni
  • 期刊名称:Journal of Emerging Trends in Computing and Information Sciences
  • 电子版ISSN:2079-8407
  • 出版年度:2010
  • 卷号:1
  • 期号:2
  • 页码:117-120
  • 出版社:ARPN Publishers
  • 摘要: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.
  • 关键词:Security; biometric process; attacks; intrusion detection; prevention; expert system.
国家哲学社会科学文献中心版权所有