期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2010
卷号：1
期号：2
出版社：Ayushmaan Technologies
摘要：Fingerprint system is an important biometric technique for personal identification. The metric used for performance of identification techniques are directly scanned fingerprints or inked impression of fingerprints. The purpose is real-time, high confidence recognition of a person's identity by mathematical analysis of the random patterns that are visible within the finger prints from some distance. Finger prints is a protected internal organ whose random texture is stable throughout life, it can serve as a kind of living password that one need not remember but one always carries along. Because the randomness of finger print patterns has very high dimensionality, recognition decisions are made with confidence levels high enough to support rapid and reliable exhaustive searches through national-sized databases. Finger print recognition has shown to be very accurate for human identification. The metric used for performance of identification techniques are directly scanned fingerprints or inked impression of fingerprints. For better accuracy in matching the images of different decomposition of matching is performed. These parameters perform better in comparing the resultant fingerprints. When tested on a database of images this system is faster and more accurate to analyze the fingerprints matching process. 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 Intrusion Detection and Prevention for human identification through fingerprints. 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.
