Authors : Sabir Umar Danillela

Volume/Issue : Volume 11 - 2026, Issue 10 - October

Google Scholar : https://tinyurl.com/244nsnu4

DOI : https://doi.org/10.38124/ijisrt/26Oct421

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The widespread use of multiple social media platforms has increased user exposure to privacy risks due to fragmented and complex privacy controls. Users are required to configure separate privacy settings across different platforms, often leading to inconsistent configurations, privacy fatigue, and unintended data disclosure. Existing privacy mechanisms remain largely platform-specific and do not provide unified or user-centred control across platforms. This study aims to design, implement, and evaluate an integrated architecture for protecting user privacy across social media platforms. The proposed system employs a Rule-Based Privacy Enforcement Algorithm (RBPEA) to translate user-defined privacy preferences into platform-specific enforcement actions. Using the Design Science Research methodology, a modular, web-based prototype was developed, incorporating secure user authentication, centralized privacy rule management, and cross-platform enforcement through platform adapters. The system was evaluated based on enforcement consistency, usability, and system performance. Results indicate improved consistency of privacy settings across platforms, reduced user effort in privacy configuration, and enhanced transparency through audit and feedback mechanisms. The findings demonstrate that algorithm-driven, integrated privacy management is both feasible and effective for improving user privacy control in multiplatform environments. This study contributes an empirically evaluated architectural model and algorithmic approach for cross-platform privacy protection, addressing a significant gap in existing privacy management solutions.

References :

1. Acquisti, A., Brandimarte, L., & Loewenstein, G. (2020). Privacy and human behaviour in the age of information. Science, 347(6221), 509–514.
2. Acquisti, A., Brandimarte, L., & Loewenstein, G. (2020). Secrets and likes: The drive for privacy and the difficulty of achieving it in the digital age. Journal of Consumer Psychology, 30(4), 736-758.
3. Barth, S., & de Jong, M. D. (2023). The privacy paradox: A systematic review of the literature. Journal of the Association for Information Science and Technology, 74(3), 299-317.
4. Bélanger, F., & Crossler, R. E. (2021). Online privacy concerns and risk beliefs: A longitudinal study. Journal of the Association for Information Systems, 22(3), 675-709.
5. Cavoukian, A. (2020). Privacy by design: Origins, meaning, and prospects. Routledge.
6. Data Reportal. (2024). Digital 2024: Global Overview Report. Kepios. Retrieved from https://datareportal.com/reports/digital-2024-global-overview-report
7. Davis, J. L., & Jurgenson, N. (2021). Context collapse and the political self in the digital age. New Media & Society, 23(5), 1095-1112.
8. Erfan, A., Garg, S., Gao, L., Yu, S., & Montgomery, J. (2017). Scoring users’ privacy disclosure across multiple online social networks. IEEE Access, 5, 13118–13130.
9. European Union. (2021). General Data Protection Regulation (GDPR): Consolidated text.
10. Fernández, E. B., & Peralta, R. (2021). Access control: Principles, models, and systems. Springer Nature.
11. Fossen, B. L., & Schweidel, D. A. (2022). Social Media and the Value of Truth. MIT Press.
12. Frimpong, S. A., Han, M., Effah, E. K., Adjei, J. K., Hanson, I., & Brown, P. (2024). A deep decentralized privacy‑preservation framework for online social networks. Blockchain: Research and Applications, 5(4), 100233. https://doi.org/10.1016/j.bcra.2024.100233 ScienceDirect
13. Ghosh, S., Majumder, P., & Sural, S. (2023). A survey on cross-platform privacy-preserving technologies. ACM Computing Surveys, 55(8), 1-35.
14. Hargittai, E., & Marwick, A. (2022). “What can I really do?” Explaining the privacy paradox with online apathy. International Journal of Communication, 16, 1227-1247.
15. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2020). Design science in information systems research. MIS Quarterly, 28(1), 75–105.
16. Irani, D., Webb, S., Li, K., & Pu, C. (2011). Modeling unintended personal‑information leakage from multiple online social networks. IEEE Internet Computing, 15(3), 14–23. MDPI
17. Isaak, J., & Hanna, M. J. (2020). User data privacy: Facebook, Cambridge Analytica, and privacy protection. IEEE Computer, 51(8), 56-59.
18. Jahid, S., Nilizadeh, S., Mittal, P., Borisov, N., & Kapadia, A. (2012). DECENT: A decentralized architecture for enforcing privacy in online social networks. In Proceedings of the Fourth IEEE International Workshop on Security and Social Networking (SESOC) (pp. 326–332). IEEE. https://doi.org/10.1109/PerComW.2012.6197504 Princeton Collaborate
19. Kang, H. (2025). Latent privacy management profiles on algorithmic social media. Journal of Computer‑Mediated Communication, 30(6). https://doi.org/10.1093/jcmc/zmaf021 Springer Link
20. Karaj, A., Macbeth, S., Berson, R., & Pujol, J. M. (2021). Whotracks.me: Shedding light on the opaque world of online tracking. Proceedings on Privacy Enhancing Technologies, 2021(2), 22-45.
21. Kosinski, M., Wang, Y., & Lakkaraju, H. (2021). Mining big data to predict psychological traits. Proceedings of the National Academy of Sciences, 118(12), e2017164118.
22. Kumar, P. (2023). Algorithmic intimacy: The datafication of personal life on TikTok. Surveillance & Society, 21(2), 178-194.
23. Li, X., Yang, Y., Chen, Y., & Niu, X. (2018). A privacy measurement framework for multiple online social networks against social identity linkage. Applied Sciences, 8(10), 1790. https://doi.org/10.3390/app8101790 MDPI
24. Liu, B., Ding, M., & Wang, H. (2023). Machine learning for privacy protection: A survey. ACM Computing Surveys, 56(2), 1-38.
25. Liu, K., & Terzi, E. (2010). A framework for computing the privacy scores of users in online social networks. ACM Transactions on Knowledge Discovery from Data, 5(1), 6. MDPI
26. Lutz, C., & Hoffmann, C. P. (2022). Privacy concerns and digital trust. Information, Communication & Society, 25(1), 1–18.
27. Mansour, E., Sambra, A. V., & Berners-Lee, T. (2021). Solid: A decentralized framework for social linked data. Proceedings of the Web Conference 2021, 223-234.
28. Mantelero, A. (2021). AI and big data: A blueprint for a human right, social and ethical impact assessment. Cambridge University Press.
29. Martin, K., & Nissenbaum, H. (2020). Measuring privacy: An ethical approach. Journal of Information Technology, 35(3), 1–15.
30. Masur, P. K. (2020). Situational privacy and online self-disclosure. Human Communication Research, 46(1), 1–28.
31. Nigeria Data Protection Regulation (NDPR). (2019). National Information Technology Development Agency (NITDA).
32. Nissenbaum, H. (2021). Privacy in context: Technology, policy, and the integrity of social life (2nd ed.). Stanford University Press.
33. Peffers, K., Tuunanen, T., Gengler, C. E., Rossi, M., Hui, W., Virtanen, V., & Bragge, J. (2020). The design science research process: A model for producing and presenting information systems research. Journal of Management Information Systems, 28(1), 45–77.
34. Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2020). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45-77.
35. Pew Research Center. (2023). Americans and Privacy: Concerned, Confused and Feeling Lack of Control Over Their Personal Information. Retrieved from https://www.pewresearch.org/internet/2023/10/15/americans-and-privacy-concerned-confused-and-feeling-lack-of-control-over-their-personal-information/
36. Regulation (EU) 2016/679 (General Data Protection Regulation - GDPR). (2016). Official Journal of the European Union, L 119, 1–88.
37. Ren, J., Jiang, L., Peng, H., Lyu, L., Liu, Z., Chen, C., Wu, J., Bai, X., & Yu, P. S. (2022). Cross‑network social user embedding with hybrid differential privacy guarantees. arXiv preprint. https://arxiv.org/abs/2209.01539 arXiv
38. Shklovski, I., Mainwaring, S., & Skúladóttir, H. (2022). Design for privacy and dignity. ACM Transactions on Computer-Human Interaction, 29(4), 1–28.
39. Shklovski, I., Mainwaring, S., & Skúladóttir, H. (2022). Design for privacy and dignity in digital systems. ACM Transactions on Computer-Human Interaction, 29(4), 1–28.
40. Shvartzshnaider, Y., Reyes, I., & Nissenbaum, H. (2022). Contextual integrity through the lens of computer science. Foundations and Trends® in Privacy and Security, 2(3), 1-69.
41. Squicciarini, A., Caragea, D., & Ross, K. (2022). Privacy policies for shared content in social networks. In Proceedings of the 20th International Conference on World Wide Web (pp. 71–80). ACM.
42. Taddeo, M., & Floridi, L. (2021). How AI can support human values. Science, 361(6404), 751–752.
43. Tikhonov, A., & Zegzhda, D. (2022). Security and privacy analysis of Telegram messenger. Proceedings of the 2022 International Conference on Engineering Management of Communication and Technology (EMCTECH), 1-5.
44. Utz, C., Degeling, M., Fahl, S., Schaub, F., & Holz, T. (2021). (Un)informed consent: Studying GDPR consent notices in the field. Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security, 973-990.
45. Van Dijck, J. (2021). The culture of connectivity: A critical history of social media. Oxford University Press.
46. Veliz, C. (2021). Privacy is power: Why and how you should take back control of your data. Penguin UK.
47. Wisniewski, P., Page, X., & Lipford, H. (2021). Improving privacy decision-making. CHI Conference Proceedings, 1–14.
48. Zaeem, R. N., & Barber, K. S. (2021). The effect of the GDPR on privacy policies: Recent progress and future promise. ACM Transactions on Management Information Systems, 12(1), 1-20.
49. Zhao, Q., Zhang, Y., & Liu, J. (2023). Mobile app privacy behaviors: A systematic analysis of third‑party SDK privacy impact. Computers & Security, 124, 102943.
50. Zheng, X., Sun, S., Mukkamala, R. R., & Vatrapu, R. (2022). Blockchain-based privacy preservation for social media. IEEE Transactions on Computational Social Systems, 9(1), 45-56.
51. Zuboff, S. (2020). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.