An Elliptic Curve-based Protocol for Privacy Preserving Frequency Computation in 2-Part Fully Distributed Setting

Privacy-preserving frequency computation is critical to privacy-preserving data mining in 2-Part Fully Distributed Setting (such as association rule analysis, clustering, and classification analysis) and has been investigated in many researches. However, these solutions are based on the Elgamal Cryp...

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Vydáno v:2020 12th International Conference on Knowledge and Systems Engineering (KSE) s. 91 - 96
Hlavní autoři: Van Vu, Thi, Luong, The Dung, Hoang, Van Quan
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 12.11.2020
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Abstract Privacy-preserving frequency computation is critical to privacy-preserving data mining in 2-Part Fully Distributed Setting (such as association rule analysis, clustering, and classification analysis) and has been investigated in many researches. However, these solutions are based on the Elgamal Cryptosystem, making computation and communication efficiency low. Therefore, this paper proposes an improved protocol using an Elliptic Curve Cryptosystem. The theoretical and experimental analysis shows that the proposed method is effective in both computing and communication compared to other methods.
AbstractList Privacy-preserving frequency computation is critical to privacy-preserving data mining in 2-Part Fully Distributed Setting (such as association rule analysis, clustering, and classification analysis) and has been investigated in many researches. However, these solutions are based on the Elgamal Cryptosystem, making computation and communication efficiency low. Therefore, this paper proposes an improved protocol using an Elliptic Curve Cryptosystem. The theoretical and experimental analysis shows that the proposed method is effective in both computing and communication compared to other methods.
Author Hoang, Van Quan
Luong, The Dung
Van Vu, Thi
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  givenname: The Dung
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  givenname: Van Quan
  surname: Hoang
  fullname: Hoang, Van Quan
  email: hoangvanquan@gmail.com
  organization: Academy of Cryptography Techniques,Director Board,Hanoi,Vietnam
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Snippet Privacy-preserving frequency computation is critical to privacy-preserving data mining in 2-Part Fully Distributed Setting (such as association rule analysis,...
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SubjectTerms 2-part fully distributed setting
Elliptic curve cryptosystem
Privacy preserving frequency computation
Privacy-preserving data mining
Secure multi-party computation
Title An Elliptic Curve-based Protocol for Privacy Preserving Frequency Computation in 2-Part Fully Distributed Setting
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