An Efficient and privacy-Preserving Biometric Identification Scheme in Cloud Computing

Abstract

Biometric identification has plays a vital role in achieving user authentication. For efficiency and economic
savings, biometric data owners are motivated to outsource the biometric data and identification tasks to a third party,
which however introduces potential threats to user’s privacy. In this paper, we propose a new privacy-preserving biometric
identification scheme which can release the database owner from heavy computation bur-den. In the proposed scheme, we
design concrete biometric data encryption and matching algorithms, and introduce perturb terms in each biometric data.
A thorough analysis indicates that our schemes are secure, and the ultimate scheme offers a high level of privacy
protection. In addition, the performance evaluations via extensive simulations demonstrate our schemes’ efficiency.