An efficient public key functional encryption for inner product evaluations
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GREEN AND HUMAN INFORMATION TECHNOLOGY 2019
An efficient public key functional encryption for inner product evaluations Intae Kim1 • Jong Hwan Park2 • Seong Oun Hwang3 Received: 25 April 2019 / Accepted: 7 August 2019 Springer-Verlag London Ltd., part of Springer Nature 2019
Abstract As many services have changed from offline to online, a lot of personal information including user private data has been collected by and exchanged with various service providers. An issue raised in this process is that personal information can be exploited by multiple unwanted entities without the data owner’s knowledge. To solve this problem, functional encryption was proposed. It is suitable for data protection because even if a third-party uses the owner’s secret key for a function f, it cannot retrieve the original message x from the ciphertext. This means that information about x cannot be published, but is exposed only as f(x), the result of the function f. However, previous pairing-based public key functional encryption schemes for inner product evaluations (FE-IPE) cannot be practical solutions yet because they require too much computation, communication and storage overheads. In this paper, we propose an efficient pairing-based public key FEIPE that requires only n (i.e., the dimension of vectors for function and message) exponentiation plus two pairing computations for decryption with smaller sized public parameters, secret keys and ciphertexts. And this scheme supports fully collusion resistance. The proposed scheme is proven selectively secure against chosen-plaintext attacks in the standard model under the external Diffie–Hellman assumption. Keywords Functional encryption Pairing-based public key functional encryption Inner product evaluation Fully collusion resistance
1 Introduction Over the past few decades, as the Internet has become widespread and deeply entrenched in our daily life, many services such as shopping and financial services have gravitated toward online. In order to support these online services in a convenient way, a lot of information including & Seong Oun Hwang [email protected] Intae Kim [email protected] Jong Hwan Park [email protected] 1
School of Computing and Information Technology, University of Wollongong, Wollongong, Australia
2
Division of Computer Science, Sangmyung University, Seoul, Korea
3
Department of Software and Communications Engineering, Hongik University, Sejong, Korea
users’ private data was collected by service providers and exchanged with other third-party service providers. Private data include an individual’s identification information, address, card number, score information, profile and history. Data stored in this way can be used for multiple purposes. Largely, an entity (e.g., service provider) that stores the data often uses it for advertising or customized services. For example, consider that employers and job seekers use online job sites. Employers prefer to get more specific information to increase the p
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