research-article

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PANDA: Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data

Authors:

Sharad Mehrotra,

Shantanu Sharma,

Jeffrey D. Ullman,

Dhrubajyoti Ghosh,

Anurag MishraAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 11, Issue 4

Article No.: 23, Pages 1 - 41

https://doi.org/10.1145/3397521

Published: 12 October 2020 Publication History

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Abstract

Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. This article continues along with the emerging trend in secure data processing that recognizes that the entire dataset may not be sensitive and, hence, non-sensitivity of data can be exploited to overcome limitations of existing encryption-based approaches. We first provide a new security definition, entitled partitioned data security, for guaranteeing that the joint processing of non-sensitive data (in cleartext) and sensitive data (in encrypted form) does not lead to any leakage. Then, this article proposes a new secure approach, entitled query binning (QB), that allows secure execution of queries over non-sensitive and sensitive parts of the data. QB maps a query to a set of queries over the sensitive and non-sensitive data in a way that no leakage will occur due to the joint processing over sensitive and non-sensitive data. In particular, we propose secure algorithms for selection, range, and join queries to be executed over encrypted sensitive and cleartext non-sensitive datasets. Interestingly, in addition to improving performance, we show that QB actually strengthens the security of the underlying cryptographic technique by preventing size, frequency-count, and workload-skew attacks.

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Index Terms

PANDA: Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data
1. Security and privacy
  1. Database and storage security

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cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 11, Issue 4

Special Issue on Analytics for Cybersecurity and Privacy, Part 1

December 2020

244 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3426166

Editor:
Daniel Zeng
Chinese Academy of Sciences, China

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Publication History

Published: 12 October 2020

Online AM: 07 May 2020

Accepted: 01 April 2020

Revised: 01 March 2020

Received: 01 November 2019

Published in TMIS Volume 11, Issue 4

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Zhang SHe XKundu AMehrotra SSharma S(2024)Secure Normal Form: Mediation Among Cross Cryptographic Leakages in Encrypted Databases2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00444(5560-5573)Online publication date: 13-May-2024
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Sharma SLi YMehrotra SPanwar NKumari KRoychoudhury S(2023)Information-Theoretically Secure and Highly Efficient Search and Row RetrievalProceedings of the VLDB Endowment10.14778/3603581.360358216:10(2391-2403)Online publication date: 1-Jun-2023
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Samanthula BKarthikeyan DDong BKumari K(2020)ESPADE: An Efficient and Semantically Secure Shortest Path Discovery for Outsourced Location-Based ServicesCryptography10.3390/cryptography40400294:4(29)Online publication date: 18-Oct-2020
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