A Privacy-Enhanced Framework for Securing User Data on Cloud-Based Social Networks

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 12

Year of Publication : 2024

Authors : S. Nasira Tabassum, Gangadhara Rao Kancherla

10.14445/23488379/IJEEE-V11I12P110

How to Cite?

S. Nasira Tabassum, Gangadhara Rao Kancherla, "A Privacy-Enhanced Framework for Securing User Data on Cloud-Based Social Networks," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 12, pp. 108-118, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I12P110

Abstract:

Online Social Networks (OSNs) have become integral to modern life, enabling people to communicate, share information, and stay connected over vast distances. However, the rising use of OSNs has sparked significant concerns regarding the privacy and security of user data. This paper presents an innovative method for strengthening data privacy and security in cloud-enabled OSNs utilizing an E-ABE system. The proposed solution employs flow graph analysis to verify relationships, ensuring secure user data exchange while offering fine-grained access control. This approach addresses the limitations of existing methods, which often fail to provide comprehensive privacy and security measures. By leveraging cryptographic techniques and secure communication protocols, the E-ABE model allows for the controlled sharing of sensitive information, ensuring that only authorized users can access data. The system's design includes roles for Cloud Service Providers (CSPs), Trusted Attribute Authorities (TAAs), and end-users (followers and followees), each contributing to the overall security framework. Experimental results demonstrate the effectiveness of the proposed method in reducing key generation time, data encryption and decryption time, and communication costs while maintaining high levels of authorization accuracy. This research contributes to the field by providing a robust solution for protecting user data in cloud-based OSNs, highlighting its potential for broader application in other domains requiring stringent data privacy and security measures.

Keywords:

OSNs, Data privacy, Data security, Attribute-Based, Encryption (ABE), Cloud computing, Flow graph analysis, Fine-grained access control.

References:

[1] Srivastava Sonam, Mahesh Kumar Singh, and Yogendra Narain Singh, “Social Media Analytics: Current Trends and Future Prospects,” Communication and Intelligent Systems, Lecture Notes in Networks and Systems, Singapore, pp. 1005-1016, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Jingwei Li et al., “Enabling Efficient and Secure Data Sharing in Cloud Computing,” Concurrency and Computation: Practice and Experience, vol. 26, no. 5, pp. 1052-1066, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Asma Siddiqua et al., “A Review and Techniques in Smart Grid for Authentication of Messages,” International Journal of Latest Engineering and Management Research, vol. 3, no. 3, pp. 91-96, 2018.
[Google Scholar] [Publisher Link]
[4] Zhiguang Qin et al., “A Survey of Proxy Re-Encryption for Secure Data Sharing in Cloud Computing,” IEEE Transactions on Services Computing, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Ahsan Saud Qadri Syed et al., “Α Chaotic Map-based Approach to Reduce Black Hole Attacks and Authentication Computational Time in MANETs,” Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 13909-13915, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Syed Shakeel Hashmi et al., “Data Hiding in the Multi-Cloud Environment by Product Cipher-Based Distributed Steganography,” Research Square, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Michael Gertz, and Sushil Jajodia, Handbook of Database Security: Applications and Trends, Springer Science and Business Media, 1st ed., New York, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Syed Shakeel Hashmi et al., “Enhancing Data Security in Multi-Cloud Environments: A Product Cipher-Based Distributed Steganography Approach,” International Journal of Safety and Security Engineering, vol. 14, no. 1, pp. 47-61, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Subashini Subashini, and Veeraruna Kavitha, “A Survey on Security Issues in Service Delivery Models of Cloud Computing,” Journal of Network and Computer Applications, vol. 34, no. 1, pp. 1-11, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Vipul Goyal et al., “Attribute-Based Encryption for Fine-Grained Access Control of Encrypted Data,” Proceedings of the 13th ACM Conference on Computer and Communications Security, New York, United States, pp. 89-98, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Bin Zhou, Jian Pei, and WoShun Luk, “A Brief Survey on Anonymization Techniques for Privacy-Preserving Publishing of Social Network Data,” ACM Sigkdd Explorations Newsletter, vol. 10, no. 2, pp. 12-22, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[12] C. Atheeq et al. “Securing UAV Networks: A Lightweight Chaotic-Frequency Hopping Approach to Counter Jamming Attacks,” IEEE Access, pp. 38685-38699, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Jin Li et al., “Identity-Based Encryption with Outsourced Revocation in Cloud Computing,” IEEE Transactions on Computers, vol. 64, no. 2, pp. 425-437, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Arthur Sandor Voundi Koe, and Yaping Lin, “Offline Privacy Preserving Proxy Re-Encryption in Mobile Cloud Computing,” Pervasive and Mobile Computing, vol. 59, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Lujun Fang, and Kristen LeFevre, “Privacy Wizards for Social Networking Sites,” Proceedings of the 19th International Conference on World Wide Web, pp. 351-360, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Elena Zheleva, and Lise Getoor, “To Join or Not to Join: The Illusion of Privacy in Social Networks with Mixed Public and Private User Profiles,” Proceedings of the 18th International Conference on World Wide Web, pp. 531-540, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[17] C. Atheeq et al., “Advancing IoT Cybersecurity: Adaptive Threat Identification with Deep Learning in Cyber-Physical Systems,” Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13559-13566, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Martin Hirt, and Kazue Sako, “Efficient Receipt-Free Voting Based on Homomorphic Encryption,” International Conference on the Theory and Applications of Cryptographic Techniques, Springer Berlin Heidelberg, pp. 539-556, 2000.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Cynthia Dwork, “Differential Privacy,” International Colloquium on Automata, Languages, and Programming, Springer Berlin Heidelberg, vol. 4052, pp. 1-12, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Rakesh Agrawal, and Ramakrishnan Srikant, “Privacy-Preserving Data Mining,” Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, pp. 439-450, 2000.
[CrossRef] [Google Scholar] [Publisher Link]
[21] C. Atheeq, and M. Munir Ahmed Rabbani, “Mutually Authenticated Key Agreement Protocol Based on Chaos Theory in Integration of Internet and MANET,” International Journal of Computer Applications in Technology, vol. 56, no. 4, pp. 309-318, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Barbara Carminati, Elena Ferrari, and Andrea Perego, “Enforcing Access Control in Web-Based Social Networks,” ACM Transactions on Information and System Security (TISSEC), vol. 13, no. 1, pp. 1-38, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Amardeep Singh, and Monika Singh, “Social Networks Privacy Preservation: A Novel Framework,” Cybernetics and Systems, vol. 55, no. 8, pp. 2356-2387, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Jiayi Chen et al., “Disclose More and Risk Less: Privacy Preserving Online Social Network Data Sharing,” IEEE Transactions on Dependable and Secure Computing, vol. 17, no. 6, pp. 1173-1187, 2018.
[CrossRef] [Google Scholar] [Publisher Link]