A probabilistic homomorphic encryption algorithm over integers - Protecting data privacy in clouds

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

With a practical homomorphic encryption algorithm, cloud service providers can operate on users' encrypted data without having to decrypt the data. Currently only one fully homomorphic encryption algorithm and some of its variants are available in literature, first developed by Graig Gentry in 2009. Unfortunately, these algorithms are not practical because of their prohibitively expensive computing cost. This paper presents an efficient homomorphic encryption algorithm which allows both arithmetic additions and multiplications on cipher texts until the data exceeds the size of the decryption key. The proposed encryption algorithm is probabilistic because every time encrypting a same plaintext it will produce a different cipher text. This probabilistic feature is useful in hiding the equality relationship among encrypted data. In this paper, we also discuss the algorithm's security weakness, which is vulnerable to some attacks. However, in some applications, the algorithm is extremely useful. This paper describes an application of a shared encrypted storage in clouds that the algorithm can be used to protect data privacy from outside attackers. At the end of the paper, we analyze the efficiency of the algorithm, and compare them to the best implementation of the Gentry-like algorithms.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
EditorsJianhua Ma, Ali Li, Huansheng Ning, Laurence T. Yang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages653-656
Number of pages4
ISBN (Electronic)9781467372114
DOIs
StatePublished - 20 Jul 2016
EventProceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015 - Beijing, China
Duration: 10 Aug 201514 Aug 2015

Publication series

NameProceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015

Conference

ConferenceProceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
Country/TerritoryChina
CityBeijing
Period10/08/1514/08/15

Keywords

  • Data privacy in clouds
  • Homomorphic encryption
  • Probabilistic encryption

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