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Secure Anonymous Query-Based Encryption for Data Privacy Preserving in Cloud: Moye(Ω)

Secure Anonymous Query-Based Encryption for Data Privacy Preserving in Cloud: Moye(Ω)

Martin Konan, Wenyong Wang
Copyright: © 2021 |Pages: 25
ISBN13: 9781799889540|ISBN10: 1799889548|EISBN13: 9781799889557
DOI: 10.4018/978-1-7998-8954-0.ch037
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MLA

Konan, Martin, and Wenyong Wang. "Secure Anonymous Query-Based Encryption for Data Privacy Preserving in Cloud: Moye(Ω)." Research Anthology on Privatizing and Securing Data, edited by Information Resources Management Association, IGI Global, 2021, pp. 815-839. https://doi.org/10.4018/978-1-7998-8954-0.ch037

APA

Konan, M. & Wang, W. (2021). Secure Anonymous Query-Based Encryption for Data Privacy Preserving in Cloud: Moye(Ω). In I. Management Association (Ed.), Research Anthology on Privatizing and Securing Data (pp. 815-839). IGI Global. https://doi.org/10.4018/978-1-7998-8954-0.ch037

Chicago

Konan, Martin, and Wenyong Wang. "Secure Anonymous Query-Based Encryption for Data Privacy Preserving in Cloud: Moye(Ω)." In Research Anthology on Privatizing and Securing Data, edited by Information Resources Management Association, 815-839. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-8954-0.ch037

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Abstract

Data privacy protection is a paramount issue in cloud applications for the last decade. In addition, data encryption, which is the primary method to impart security in clouds, is proved insufficient to guarantee data privacy protection from some security issues like homogeneity and background knowledge attacks. Therefore, it is important to provide a security mechanism that provide not only anonymous data but also anonymous continuous queries. So, this paper proposes a new scheme (Moye) that tackles this challenge by protecting queries to be linked to specific sensitive data. Specifically, the proposed solution is based on the design of a hybrid implementation of public key encryption with keyword search (PEKS) and subset membership encryption (SME) cryptosystem to enhance both data and query privacy protection. In addition, this approach provides an efficient and anonymous data processing by using an optimized k-anonymity scheme. Doing so, the authors protect searchable keywords and queries from inside and outside guessing attacks for the effectiveness of the proposed solution.

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