Secure key agreement using pure biometrics

In this thesis, we propose a novel secure key agreement protocol that uses biometrics with unordered set of features. Our protocol enables the user and the server to agree on a symmetric key, which is generated by utilizing only the feature points of the user's biometrics. It means that our protocol does not generate the key randomly or it does not use any random data in the key itself. As a proof of concept, we instantiate our protocol model using ngerprints. In our protocol, we employ a threshold-based quantization mechanism, in order to group the minutiae in a prede ned neighborhood. In this way, we increase the chance of user-server agreement on the same set of minutiae. Our protocol works in rounds. In each round, depending on the calculated similarity score on the common set of minutiae, the acceptance/rejection decision is made. Besides, we employ multi-criteria security analyses for our proposed protocol. These security analyses show that the generated keys possess acceptable randomness according to Shannon's entropy. In addition, the keys, which are generated after each protocol run, are indistinguishable from each other, as measured by the Hamming distance metric. Our protocol is also robust against brute-force, replay and impersonation attacks, proven by high attack complexity and low equal error rates. At the end, the complexity analysis and the memory requirements of the protocol are discussed and it is showed that they are in acceptable limits. As shown by comparative analyses, this work outperforms the existing fuzzy vault method in terms of veri cation performance and the attack complexity

Secure key agreement using pure biometrics

In this paper, we propose a novel secure key agreement protocol that uses biometrics with unordered set of features. Our protocol enables the user and the server to agree on a symmetric key, which is generated by utilizing only the feature points of the user's biometrics. It means that our protocol does not generate the key randomly or it does not use any random data in the key itself. As a proof of concept, we instantiate our protocol model using fingerprints. In our protocol, we employ a threshold-based quantization mechanism, in order to group the minutiae in a predefined neighborhood. In this way, we increase the chance of user-server agreement on the same set of minutiae. Our protocol works in rounds. In each round, depending on the calculated similarity score on the common set of minutiae, the acceptance/rejection decision is made. Besides, we employ multi-criteria security analyses for our proposed protocol. These security analyses show that the generated keys possess acceptable randomness according to Shannon's entropy. In addition, the keys, which are generated after each protocol run, are indistinguishable from each other, as measured by the Hamming distance metric. Our protocol is also robust against brute-force, replay and impersonation attacks, proven by high attack complexity and low equal error rates

On the use of ordered biometric features for secure key agreement

In this work, we propose a novel secure key agreement protocol, Secure Key Agreement using Pure Ordered Biometrics (SKA-POB), in which the cryptographic keys are generated using an ordered set of biometrics, without any other helper data. The proposed approach is realized using iris biometrics. Our protocol makes use of hash functions, and we propose a window-based comparison strategy and a window reset method. This way, performance is maximized without sacrificing security. SKA-POB protocol works in round manner, allowing to successfully terminate with key establishment as early as possible so that the complexity is reduced for both client and server sides. Additionally, we employ multi-criteria analyses for our proposed SKA-POB protocol and we provide verification results in terms of performance analysis together with randomness, distinctiveness and attack complexity through security analysis. Results show that highly random and secure keys can be generated with almost no error and with very low complexity

Secure key agreement based on ordered biometric features

In this work, we propose a novel secure key agreement protocol, Secure Key Agreement using Pure Ordered Biometrics (SKA-POB), in which the cryptographic keys are generated using an ordered set of biometrics, without any extra shared secret data or keys. The proposed approach is instantiated using iris biometrics. Our protocol makes use of hash functions and HMAC (Hash-based Message Authentication Code) as the only cryptographic primitives; thus, it is not cryptographically resource-hungry. We also propose and integrate a window-based comparison strategy and a window reset method in SKA-POB. This way, performance is maximized without sacrificing security. Furthermore, we propose an intelligent fake block generation and distribution strategy to hide the genuine blocks in transit, which increases the resistence of our proposed protocol against correlation attacks. SKA-POB protocol works in round manner, allowing to successfully terminate with key establishment as early as possible so that the complexity is reduced for both client and server sides. Additionally, we employ multi-criteria analyses for our proposed SKA-POB protocol and we provide verification results in terms of performance analysis together with randomness, distinctiveness and attack complexity through security analysis. Results show that highly random and computationally secure keys can be generated with almost no error and with very low complexity

SKA-CaNPT: secure key agreement using cancelable and noninvertible biometrics based on periodic transformation

Nowadays, many of the security-providing applications use biometrics-based authentication. However, since each person's biometrics is unique and non-replaceable, once it is compromised, it will be compromised forever. Therefore, it is hard for the users to trust biometrics. To overcome this problem, in this paper, we propose a novel secure key agreement protocol SKA-CaNPT. Here, we use a periodic transformation function to make biometrics cancelable and noninvertible. At the very end of our SKA-CaNPT protocol, the user and the server make an agreement on a symmetric shared key that is based on the feature points of the user's biometrics. Therefore, if the transformed data is compromised, then just by changing one of the inputs of the transformation function, we can renew the cryptographic key. As a proof of concept, we apply our SKA-CaNPT protocol on fingerprints. Besides, we apply different security analyses on our protocol. We use Shannon's entropy and Hamming distance metrics to analyze the randomness and the distinctiveness of the agreed keys. Moreover, according to the low IKGR (Incorrect Key Generation Rate), high CKGR (Correct Key Generation Rate) and high attack complexity possessed by our SKA-CaNPT protocol, we can conclude that our scheme is secure against brute-force, replay and impersonation attacks

Physiological signal database

Physiological signal database has been created for research purposes and required to be used for the same purpose. This database is described in D. Karaoğlan Altop, A. Levi and V. Tuzcu. "SU-PhysioDB: A physiological signals database", submitted to IEEE BlackSeaCom, June 2017. Users are required to cite this publication when referencing this material. Interested researchers may obtain the database by agreeing these requirements. For further details and for downloading the database please refer to http://people.sabanciuniv.edu/levi/projects/114E557

Secure key agreement protocols: pure biometrics and cancelable biometrics

In this paper, we propose two novel biometrics-based secure key agreement protocols, namely Secure Key Agreement-Pure Biometrics (SKA-PB) and Secure Key Agreement-Cancelable Biometrics (SKA-CB). Each of our protocols uses biometrics with unordered features. SKA-PB protocol provides symmetric cryptographic key agreement between the user and the server. This key is generated by utilizing only the feature points of the user’s biometrics. In other words, SKA-PB protocol does not generate the key randomly or it does not use any random data in the key itself. On the other hand, SKA-CB protocol integrates the cancelability property into SKA-PB protocol by the use of a device-specific binary string. In SKA-CB protocol, biometric templates can be canceled at any time as a precaution to template compromise. As a proof of concept, we implement these protocols using fingerprints and employ multi-criteria security and complexity analyses for both of them. These security analyses show that the generated keys possess sufficient randomness according to Shannon’s entropy. Additionally, these keys are distinct from each other, as measured by Hamming distance metric. Our protocols are also robust against brute-force, replay and impersonation attacks, proven by high attack complexity and low error rates

Characteristics of patients with hepatocellular carcinoma: A multicenter study

Background and Aim: The aim of the present study was to examine the etiology of hepatocellular carcinoma (HCC) by underlying cause and determine the characteristics and clinical features of patients with HCC. Materials and Methods: The study comprised 1802 HCC patients diagnosed and followed up by Liver Diseases Outpatient Clinics in 14 tertiary centers in Turkey between 2001 and 2020. Results: The mean age was 62.3 +/- 10.7 years, and 78% of them were males. Of the patients, 82% had cirrhosis. Hepatitis B virus (HBV) infection was the most common etiology (54%), followed by hepatitis C virus (HCV) infection (19%) and nonalcoholic fatty liver disease (NAFLD) (10%). Of the patients, 56% had a single lesion. Macrovascular invasion and extrahepatic spread were present in 15% and 12% of the patients, respectively. The median serum alpha-fetoprotein level was 25.4 ng/mL. In total, 39% of the patients fulfilled the Milan Criteria. When we compared the characteristics of patients diagnosed before and after January 2016, the proportion of NAFLD-related HCC cases increased after 2016, from 6.6% to 13.4%. Conclusion: Chronic HBV and HCV infections remain the main causes of HCC in Turkey. The importance of NAFLD as a cause of HCC is increasing