scholarly journals Fast Vector Oblivious Linear Evaluation from Ring Learning with Errors

2021 ◽  
Author(s):  
Leo de Castro ◽  
Chiraag Juvekar ◽  
Vinod Vaikuntanathan
Keyword(s):  
Author(s):  
Marius Iulian Mihailescu ◽  
Stefania Loredana Nita
Keyword(s):  

Author(s):  
Miruna Roşca ◽  
Amin Sakzad ◽  
Damien Stehlé ◽  
Ron Steinfeld
Keyword(s):  

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bo Mi ◽  
Ping Long ◽  
Yang Liu ◽  
Fengtian Kuang

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.


Author(s):  
Shi Bai ◽  
Dipayan Das ◽  
Ryo Hiromasa ◽  
Miruna Rosca ◽  
Amin Sakzad ◽  
...  
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Author(s):  
Chandrakala B M ◽  
S C Lingareddy

<p>In recent days, data sharing has provided the flexibility to share the data, store the data, and perform operation on data virtually as well as cost effectively. Data sharing in cloud is one of the feature, which is being popular and widely accepted. However, the concern here is to ensure the data security and this has led the researcher to research in this area. To provide the security several Proxy re-encryption scheme has been introduced, however all these method lacks of efficiency. Hence In this paper, we propose a scheme known as ALBC (Adaptive Lattice Based Cryptography), this scheme follows the two phase i.e. encryption and Re-encryption. Encryption phase has few algorithms such as Key_Gen, Enc, Dec. Similarly ALBC Re-Enc has five algorithm i.e. Key_Gen, Key_ReGen,  Enc, Re-Enc, Dec. our algorithm not only provides the security but also solves the problem of RL(Ring-learning) with errors problems. In order to evaluate, our algorithm is compared with the existing model in terms of encryption time, decryption time, re-encryption time, key generation  and key regeneration by varying the various key size. When we observe the comparative analysis, it is observed that our algorithm outperforms the existing algorithm.</p>


Author(s):  
Zvika Brakerski ◽  
Elena Kirshanova ◽  
Damien Stehlé ◽  
Weiqiang Wen
Keyword(s):  

Author(s):  
Rohit Chatterjee ◽  
Sanjam Garg ◽  
Mohammad Hajiabadi ◽  
Dakshita Khurana ◽  
Xiao Liang ◽  
...  

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