Proceedings Article10.1145/2896387.2896423
Efficient Security Framework for Sensitive Data Sharing and Privacy Preserving on Big-Data and Cloud Platforms
Priya Dudhale Pise,Nilesh J. Uke +1 more
- 22 Mar 2016
- pp 38
9
TL;DR: This paper is presenting the novel hybrid framework for secure sensitive data sharing and privacy preserving public auditing for shared data over big data systems including functionalities such as privacy preserving, public Auditing, data security, storage, data access, deletion or secure data destruction using cloud services.
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Abstract: Now day's use of big data platforms is increasing for storing large amount of end user's data remotely on big data servers. Cloud computing storage was widely used for storing user's data, but cloud computing only providing the tasks of data storage but not supporting the important functionalities like computation and database operations. These operations are supported by big data systems and hence currently use of big data platform for storage in increases worldwide by enterprises. Sharing sensitive information and data resulted into big reduction in costs of enterprises for users to provide value added data and personalized services. As enterprises are sharing their important and sensitive information on big data platforms from different and many domains, it becomes necessary to provide the security and privacy in big data platform. Data security and privacy is gaining significant attentions of researchers. There are many security methods already proposed for cloud computing platform, now same methods slowly adopted on big data platform. For Big Data platforms, secure sharing of sensitive data is challenging research problem. In this paper, first we are introducing the different security and privacy preserving methods of cloud computing and big data platforms with their limitations, and then presenting the novel hybrid framework for secure sensitive data sharing and privacy preserving public auditing for shared data over big data systems including functionalities such as privacy preserving, public auditing, data security, storage, data access, deletion or secure data destruction using cloud services.
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Citations
Analyzing and Evaluating Critical Challenges and Practices for Software Vendor Organizations to Secure Big Data on Cloud Computing: An AHP-Based Systematic Approach
Abudul Wahid Khan,Maseeh Ullah Khan,Javed Ali Khan,Arshad Ahmad,Khalil Khan,Muhammad Zamir,Wonjoon Kim,Muhammad Fazal Ijaz +7 more
TL;DR: In this article, the authors conducted a systematic literature review (SLR) through which they have find out 103 relevant research publications by developing a search string that is inspired by the research questions.
A data privacy protection scheme for Internet of things based on blockchain
Gong Jing,Mei Yurong,Feng Xiang,Hong Hanshu,Sun Yibo,Zhixin Sun +5 more
- 01 May 2021
TL;DR: This article combines blockchain technology with ring signature and proxy reencryption to propose a privacy protection solution for the IoT, and the distributed ledger eases the pressure of mass data storage on a centralized server.
13
Hybrid Encryption Techniques for Secure Sharing of a Sensitive Data for Banking Systems Over Cloud
Prachi More,Shubham Chandugade,Shaikh Mohammad Shafi Rafiq,Priya Pise +3 more
- 01 Feb 2018
TL;DR: This work shows a security framework that can give protection and uprightness to trading delicate data through the cloud or the correspondence systems, in view of the utilization of the combination of Attribute-Based Encryption and Byte Rotation Encryption Algorithm.
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Cost-effective internet of things privacy-aware data storage and real-time analysis
Femi.A. Elegbeleye,Munienge Mbodila,Omobayo A. Esan,I. Elegbeleye +3 more
TL;DR: The results obtained show that the combination of two data privacy models: differential privacy and k-anonymity models performed better than any individual model and any other combined models in the protection of users’ personal information.
References
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TL;DR: In this paper, the problem of identity-based proxy re-encryption is addressed, where ciphertexts are transformed from one identity to another without seeing the underlying plaintext.
Big data security
TL;DR: Controls need to be placed around the data itself, rather than the applications and systems that store the data, to ensure it's secure in the process, says Colin Tankard of Digital Pathways.
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Privacy-Preserving Ciphertext Multi-Sharing Control for Big Data Storage
TL;DR: A privacy-preserving ciphertext multi-sharing mechanism that combines the merits of proxy re-encryption with anonymous technique in which a ciphertext can be securely and conditionally shared multiple times without leaking both the knowledge of underlying message and the identity information of ciphertext senders/recipients is proposed.
Secure sensitive data sharing on a big data platform
TL;DR: A proxy re-encryption algorithm based on heterogeneous ciphertext transformation and a user process protection method based on a virtual machine monitor are presented, which provides support for the realization of system functions and protects the security of users' sensitive data effectively and shares these data safely.
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Multi-use unidirectional identity-based proxy re-encryption from hierarchical identity-based encryption
Jun Shao,Zhenfu Cao +1 more
TL;DR: A conversion from non-anonymous hierarchical identity-based encryption (NaHIBE) with strongly CPA security to CCA-secure and collusion-resistant MUIBPRE, which is based on the NaHibE scheme proposed by Waters at Crypto'09, is presented.
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