scholarly journals Functional encryption for cascade automata

2017 ◽  
Vol 255 ◽  
pp. 384-407
Author(s):  
Dan Brownstein ◽  
Shlomi Dolev ◽  
Niv Gilboa
Keyword(s):  
Functional Encryption

Simple and Generic Constructions of Succinct Functional Encryption

2021 ◽  
Vol 34 (3) ◽  
Author(s):  
Fuyuki Kitagawa ◽  
Ryo Nishimaki ◽  
Keisuke Tanaka
Keyword(s):  
Functional Encryption

Functional encryption for computational hiding in prime order groups via pair encodings

2017 ◽  
Vol 86 (1) ◽  
pp. 97-120 ◽  
Author(s):  
Jongkil Kim ◽  
Willy Susilo ◽  
Fuchun Guo ◽  
Man Ho Au
Keyword(s):  
Prime Order ◽  
Functional Encryption

scholarly journals Power of public-key function-private functional encryption

2018 ◽  
Vol 12 (4) ◽  
pp. 248-256
Author(s):  
Vincenzo Iovino ◽  
Qiang Tang ◽  
Karol Żebrowski
Keyword(s):  
Public Key ◽  
Functional Encryption

scholarly journals Balancing Access Control and Privacy for Data Deduplication via Functional Encryption

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bo Mi ◽  
Ping Long ◽  
Yang Liu ◽  
Fengtian Kuang
Keyword(s):  
Access Control ◽  
Security Analysis ◽  
Functional Encryption ◽  
Data Deduplication ◽  
Paper Briefly ◽  
Storage Security ◽  
Redundancy Removal ◽  
Proof Of Ownership ◽  
Learning With Errors ◽  
And Storage

Data deduplication serves as an effective way to optimize the storage occupation and the bandwidth consumption over clouds. As for the security of deduplication mechanism, users’ privacy and accessibility are of utmost concern since data are outsourced. However, the functionality of redundancy removal and the indistinguishability of deduplication labels are naturally incompatible, which bring about a lot of threats on data security. Besides, the access control of sharing copies may lead to infringement on users’ attributes and cumbersome query overheads. To balance the usability with the confidentiality of deduplication labels and securely realize an elaborate access structure, a novel data deduplication scheme is proposed in this paper. Briefly speaking, we drew support from learning with errors (LWE) to make sure that the deduplication labels are only differentiable during the duplication check process. Instead of authority matching, the proof of ownership (PoW) is then implemented under the paradigm of inner production. Since the deduplication label is light-weighted and the inner production is easy to carry out, our scheme is more efficient in terms of computation and storage. Security analysis also indicated that the deduplication labels are distinguishable only for duplication check, and the probability of falsifying a valid ownership is negligible.

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