Privacy-preserving search in data clouds using normalized homomorphic encryption

Mohanad Dawoud*, D. Turgay Altilar

*Corresponding author for this work

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

9 Citations (Scopus)


By the rapid growth of computer systems, many IT applications that rely on cloud computing have appeared; one of these systems is the data retrieval systems, which need to satisfy various requirements such as the privacy of the data in the cloud. There are many proposed Privacy-Preserving search (PPS) techniques that uses homomorphic encryption to process the data after encryption, but these techniques did not take into account the possibility of repetition of some values of the features table (especially zero), even after the encryption, which makes them vulnerable to frequency attacks. On the other hand, the non-inclusion of these values may lead to the ability to infer some statistical information about the data. In this paper, we took the advantages of homomorphic encryption to encrypt the data as well as preventing any ability to infer any kind of information about the data by normalizing the histogram of the features table while maintaining the quality of the retrieval. The results showed that the proposed technique gave better retrieval efficiency than the previously proposed techniques while preventing frequency attacks.

Original languageEnglish
Title of host publicationEuro-Par 2014
Subtitle of host publicationParallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers
EditorsLuís Lopes
PublisherSpringer Verlag
Number of pages11
ISBN (Electronic)9783319143125
Publication statusPublished - 2014
EventInternational Workshop on Parallel Processing, Euro-Par 2014 - Porto, Portugal
Duration: 25 Aug 201426 Aug 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Workshop on Parallel Processing, Euro-Par 2014

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2014.


  • Data clouds
  • Data retrieval
  • Frequency attacks
  • Homomorphic encryption
  • Normalization
  • Security


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