Privacy-preserving search in data clouds using normalized homomorphic encryption

Mohanad Dawoud; D. Turgay Altilar

doi:10.1007/978-3-319-14313-2_6

Privacy-preserving search in data clouds using normalized homomorphic encryption

Mohanad Dawoud^*, D. Turgay Altilar

^*Corresponding author for this work

Department of Computer Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Euro-Par 2014
Subtitle of host publication	Parallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers
Editors	Luís Lopes
Publisher	Springer Verlag
Pages	62-72
Number of pages	11
ISBN (Electronic)	9783319143125
DOIs	https://doi.org/10.1007/978-3-319-14313-2_6
Publication status	Published - 2014
Event	International Workshop on Parallel Processing, Euro-Par 2014 - Porto, Portugal Duration: 25 Aug 2014 → 26 Aug 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8806
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Workshop on Parallel Processing, Euro-Par 2014
Country/Territory	Portugal
City	Porto
Period	25/08/14 → 26/08/14

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2014.

Keywords

Data clouds
Data retrieval
Frequency attacks
Homomorphic encryption
Normalization
Security

Access to Document

10.1007/978-3-319-14313-2_6

Cite this

Dawoud, M., & Altilar, D. T. (2014). Privacy-preserving search in data clouds using normalized homomorphic encryption. In L. Lopes (Ed.), Euro-Par 2014: Parallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers (pp. 62-72). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8806). Springer Verlag. https://doi.org/10.1007/978-3-319-14313-2_6

Dawoud, Mohanad ; Altilar, D. Turgay. / Privacy-preserving search in data clouds using normalized homomorphic encryption. Euro-Par 2014: Parallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers. editor / Luís Lopes. Springer Verlag, 2014. pp. 62-72 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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.",

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Dawoud, M & Altilar, DT 2014, Privacy-preserving search in data clouds using normalized homomorphic encryption. in L Lopes (ed.), Euro-Par 2014: Parallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8806, Springer Verlag, pp. 62-72, International Workshop on Parallel Processing, Euro-Par 2014, Porto, Portugal, 25/08/14. https://doi.org/10.1007/978-3-319-14313-2_6

Privacy-preserving search in data clouds using normalized homomorphic encryption. / Dawoud, Mohanad; Altilar, D. Turgay.
Euro-Par 2014: Parallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers. ed. / Luís Lopes. Springer Verlag, 2014. p. 62-72 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8806).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Dawoud M, Altilar DT. Privacy-preserving search in data clouds using normalized homomorphic encryption. In Lopes L, editor, Euro-Par 2014: Parallel Processing Workshops - Euro-Par 2014 InternationalWorkshops, Revised Selected Papers. Springer Verlag. 2014. p. 62-72. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-14313-2_6

Privacy-preserving search in data clouds using normalized homomorphic encryption

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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