Improving Security Using A Biometrics Approach And Encryption

The contemporary personal security structures can be collected in a few categories. Traditional personal authentication systems that are based on knowledge (Password, Username...) or physical tokens (ID card, Passport, Student Card...) are not able to meet strict security performance requirements of a number of modern applications. These applications generally make use of computer networks (Internet, Local LAN..), affect a large portion of the population, and control financially valuable and privacy-related tasks (e-commerce, e-banking, e-government...). Biometrics-based authentication systems that use physiological and/or behavioral traits (fingerprint, face, signature...) are good alternatives to traditional methods. These systems are more reliable (biometric data can not be lost, forgotten, or guessed) and more user-friendly (there is nothing to remember or carry). Hence the usage of biometric systems becomes more common day by day. For example, the UN announced that all countries must change their passport security structures to biometrics systems till2014.In this Master thesis I will focus on biometric systems, namely;what is biometrics? How does it function? How can it be used for security? I will also elaborate on practical examples. The main drive of the thesis is how can biometrics be integrated to other security systems? What are the vulnerabilities, threats, and attacks? Hence I will focus on the usage of encryption systems and their integration into biometrics systems, and try to elaborate on an approach combining the two systems together. I will explain the MD5and SHA-1algorithm, and the MD5and SHA-1use for biometrics encryption, highlighting MD5&SHA-1encryption tools usage for producing MD5and SHA-1hash key from biometric data. These biometric data will be derived by using ROI (region of interest) extracted image, meaning that when getting an image from finger or iris:how it focuses on region point to get the image. Like a finger print image minutiae points, iris is normalized. These biometric features will be converted to machine language.