Fujitsu tech turns biometric data into a cryptographic key

2015 ◽  
Vol 2015 (11) ◽  
pp. 3
2020 ◽  
Vol 38 (3B) ◽  
pp. 115-127
Author(s):  
Duha D. Salman ◽  
Raghad A. Azeez ◽  
Adul mohssen J. Hossen

Biometrics are short of revocability and privacy while cryptography cannot adjust the user’s identity.  By obtaining cryptographic keys using biometrics, one can obtain the features such as revocability, assurance about user’s identity, and privacy. Multi-biometrical based cryptographic key generation approach has been proposed, subsequently, left and right eye and ear of a person are uncorrelated from one to other, and they are treated as two independent biometrics and combine them in our system. None-the-less, the encryption keys are produced with the use of an approach of swarm intelligence.  Emergent collective intelligence in groups of simple autonomous agents is collectively termed as a swarm intelligence. The Meerkat Clan Key Generation Algorithm (MCKGA) is a method for the generation of a key stream for the encryption of the plaintext. This method will reduce and distribute the number of keys.  Testing of system, it was found that the keys produced by the characteristics of the eye are better than the keys produced by the characteristics of the ear. The advantages of our approach comprise generation of strong and unique keys from users’ biometric data using MCKGA and it is faster and accurate in terms of key generation.


2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Minhye Seo ◽  
Jong Hwan Park ◽  
Youngsam Kim ◽  
Sangrae Cho ◽  
Dong Hoon Lee ◽  
...  

Biometric data is user-identifiable and therefore methods to use biometrics for authentication have been widely researched. Biometric cryptosystems allow for a user to derive a cryptographic key from noisy biometric data and perform a cryptographic task for authentication or encryption. The fuzzy extractor is known as a prominent biometric cryptosystem. However, the fuzzy extractor has a drawback in that a user is required to store user-specific helper data or receive it online from the server with additional trusted channel, to derive a correct key. In this paper, we present a new biometric-based key derivation function (BB-KDF) to address the issues. In our BB-KDF, users are able to derive cryptographic keys solely from their own biometric data: users do not need any other user-specific helper information. We introduce a security model for the BB-KDF. We then construct the BB-KDF and prove its security in our security model. We then propose an authentication protocol based on the BB-KDF. Finally, we give experimental results to analyze the performance of the BB-KDF. We show that our proposed BB-KDF is computationally efficient and can be deployed on many different kinds of devices.


2018 ◽  
Vol 5 (4) ◽  
pp. 1-5
Author(s):  
Na Yea Oh ◽  
Hee Soo Kim ◽  
Jin Wan Park
Keyword(s):  

Author(s):  
Igor I. Koltunov ◽  
Anton V. Panfilov ◽  
Ivan A. Poselsky ◽  
Nikolay N. Chubukov ◽  
Ivan V. Krechetov ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document