CloudProtect: Managing Data Privacy in Cloud Applications

Author(s):  
Mamadou H. Diallo ◽  
Bijit Hore ◽  
Ee-Chien Chang ◽  
Sharad Mehrotra ◽  
Nalini Venkatasubramanian



Author(s):  
Martin Konan ◽  
Wenyong Wang

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.



2018 ◽  
Vol 12 (4) ◽  
pp. 1-23 ◽  
Author(s):  
Martin Konan ◽  
Wenyong Wang

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.



Author(s):  
P. Sudheer ◽  
T. Lakshmi Surekha

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been to secure the cloud storage. Data content privacy. A semi anonymous privilege control scheme AnonyControl to address not only the data privacy. But also the user identity privacy. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. The  Anonymity –F which fully prevent the identity leakage and achieve the full anonymity.







2019 ◽  
Author(s):  
Angela G. Winegar ◽  
Cass R. Sunstein




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