Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    Regression Via Classification for Fingerprint Orientation Estimation
    (Ieee-inst Electrical Electronics Engineers inc, 2024) Erdogmus, Nesli
    Estimating the direction in which the ridges and valleys of the fingerprint pattern are aligned often serves as a pivotal first step in fingerprint recognition systems. The ridge orientation map is a fundamental reference for subsequent processing stages, such as image enhancement, feature extraction, and matching. Therefore, its accuracy is essential to achieve high recognition rates. Ridge orientation estimation entails a regression problem since the task is to estimate an angle between 0 degrees and 180 degrees for each sub-region in the fingerprint image. However, the majority of the approaches in the literature pivot towards framing this regression task as a classification problem. This paper systematically analyzes the regression via classification methodology for fingerprint orientation estimation, exploring various discretization and encoding strategies. Specifically, we examine single and multiple discretization schemes designed to ensure that resulting bins maintain uniform length or uniform probability or are allocated randomly, paired with one-hot, ordinal, and cyclic encoding techniques. Our experiments are conducted on the FOE-TEST database from FVC-onGoing, the sole publicly available fingerprint orientation dataset. The findings highlight the efficacy of cyclic encoding over the one-hot encoding prevalent in prior research, while equal-length and equal-probability discretization strategies yield comparable results.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 9
    P/Key: Puf Based Second Factor Authentication
    (Public Library of Science, 2023) Uysal, Ertan; Akgün, Mete
    One-time password (OTP) mechanisms are widely used to strengthen authentication processes. In time-based one-time password (TOTP) mechanisms, the client and server store common secrets. However, once the server is compromised, the client’s secrets are easy to obtain. To solve this issue, hash-chain-based second-factor authentication protocols have been proposed. However, these protocols suffer from latency in the generation of OTPs on the client side because of the hash-chain traversal. Secondly, they can generate only a limited number of OTPs as it depends on the length of the hash-chain. In this paper, we propose a second-factor authentication protocol that utilizes Physically Unclonable Functions (PUFs) to overcome these problems. In the proposed protocol, PUFs are used to store the secrets of the clients securely on the server. In case of server compromise, the attacker cannot obtain the seeds of clients’ secrets and can not generate valid OTPs to impersonate the clients. In the case of physical attacks, including side-channel attacks on the server side, our protocol has a mechanism that prevents attackers from learning the secrets of a client interacting with the server. Furthermore, our protocol does not incur any client-side delay in OTP generation.