Paper 2020/264

Plaintext Recovery Attacks against Linearly Decryptable Fully Homomorphic Encryption Schemes

Nicholas Mainardi, Alessandro Barenghi, and Gerardo Pelosi

Abstract

Homomorphic encryption primitives have the potential to be the main enabler of privacy preserving computation delegation to cloud environments. One of the avenues which has been explored to reduce their significant computational overhead with respect to cleartext computation is the one of the so-called noise-free homomorphic encryption schemes. In this work, we present an attack against fully homomorphic encryption primitives where a distinguisher for a single plaintext value exists. We employ two noise-free homomorphic encryption schemes where such a property holds as our case studies, providing detailed attack procedure against them. We validate the effectiveness and performance of our attacks on prototype implementations of the said schemes, and suggest two countermeasures to our attack tailored to the schemes at hand.

Note: The final version of this work is published in the International Journal of Computers & Security, Volume 87, November 2019. DOI: https://doi.org/10.1016/j.cose.2019.101587

Metadata
Available format(s)
PDF
Category
Public-key cryptography
Publication info
Published elsewhere. Minor revision. International Journal of Computers & Security, Volume 87
DOI
10.1016/j.cose.2019.101587
Keywords
cryptanalysisfully homomorphic encryptionplaintext-recovery attack
Contact author(s)
nicholas mainardi @ polimi it
History
2020-03-04: received
Short URL
https://ia.cr/2020/264
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2020/264,
      author = {Nicholas Mainardi and Alessandro Barenghi and Gerardo Pelosi},
      title = {Plaintext Recovery Attacks against Linearly Decryptable Fully Homomorphic Encryption Schemes},
      howpublished = {Cryptology ePrint Archive, Paper 2020/264},
      year = {2020},
      doi = {10.1016/j.cose.2019.101587},
      note = {\url{https://eprint.iacr.org/2020/264}},
      url = {https://eprint.iacr.org/2020/264}
}
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