Converting Fingerprint Local Features to Public Key Using Fuzzy Extractor Mohammed S. Khalil 1 and Dzulkifli Muhammad 1 , M.Masroor Ahmed 2 1 Department of Computer Graphics and Multimedia, Universiti Teknologi Malaysia, sayimkhalil@gmail.com 1 Department of Computer Graphics and Multimedia, Universiti Teknologi Malaysia, dzulkifli@utm.my 2 Department of Computer Graphics and Multimedia, Universiti Teknologi Malaysia, masroorahmed@gmail.com ABSTRACT Biometric security systems are being widely used for ensuring maximum level of safety. In Biometric system, neither the data is uniformly distributed, nor can it be reproduced precisely. Each time it is processed. However, this processed data cannot be used as a password or as a cryptography secret. This paper proposes a novel method to extract fingerprint minutiae features and converting it to a public key using the fuzzy extractor. The public key can be used as a key in a cryptographic application Keywords: Biometric, Fingerprint, Local feature, Fuzzy extractor, and Cryptography. 1. Introduction Biometric system ensures an automatic identification of human being based on the principle of measureable physiological or behavioral characteristics such as fingerprint, an iris pattern, or a voice sample [1]. A significant feature associated with Biometric data is that: it is hard to forge, unique to each person, and excellent source of entropy which makes them an excellent candidate for security applications. However, they have some disadvantage, such as biometric data cannot be subjected to any change, biometric template easy to steal, the data are not uniformly distributed and exactly reproducible, they cannot be used directly as password or cryptography secret [2]. When biometric data are used in an application it has to be stored in a database. This data might be used across a network for matching against reference database. Due to this basic step, the biometric system gets exposed to a new security risk such as: constructing false biometrics from stolen biometric template, and stolen biometric data are stolen for life [3]. There have been several researches in the literature addressing this issue [4; 5; 6; 7]. Juels and Wattenberg [8] presented the first fuzzy commitment sachems by combining well- known techniques from the areas of error- correcting codes and cryptography, in which a cryptographic key is de-committed using biometric data. Though this scheme worked well, but it has two major shortcomings; first, it does not allow modifications of the key. Second, the security proof holds if the key is uniformly distributed. Juels and sudan fixed these drawbacks by proposing a fuzzy vault scheme [9]. The main drawback of this scheme is that if it’s used for different application with different vault each times it reveals fingerprint minutiae. To overcome the drawback of the fuzzy commitment and the fuzzy vault Yevgeniy et al [10] defined a fuzzy extractor, which will be used in this paper to convert the fingerprint local feature