1 DataOpus, Database Security Department, Hpuston, Texas, United State of America.
2 Veritas University, Software Engineering Department, Bwari, Abuja, FCT, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 23(03), 2687–2696
Received on 09 August 2024; revised on 21 September 2024; accepted on 23 September 2024
The research is conducted to investigate how AI transforms the notion of protection of privacy through discussing the status quo technologies, challenges, and future directions. All due to the sudden rise of digital data, protection of personal information has evolved as a major concern for which AI-enabled solutions are being introduced. Advanced concepts of AI are therefore marking the paradigm shift in how organizations handle sensitive data, letting more secure and privacy-oriented practices lead the way with notions such as differential privacy, federated learning, and anomaly detection. However, despite these advances, formidable challenges remain regarding the opacity of AI models, possible algorithmic biases, and regulatory compliance. The paper further discusses the future of AI for privacy protection, with new developments: XAI, integration of AI with blockchain, and quantum-resistant cryptography. These advances offer great transparency, security, and responsibility in privacy management. It further underlines that the collaboration of governments, industrial leaders, and researchers is required in providing appropriate frameworks for the usage of AI, given the ethical and regulatory concerns around privacy protection as the influence of AI grows. While AI is indeed very promising in improving privacy protections, the degree to which it can actually function depends on the surmounting of present limitations and harmonization of technological development with shifting data privacy criteria. The AI in this research paper will continue to play a leading role in shaping the future of privacy preservation, with answers continuing to emanate from innovation, security, and ethical concerns. It is through continuous improvement and collaboration that AI can ensure effective privacy measures in an increasingly data-driven world.
AI-powered privacy protection; Differential privacy; Federated learning; Explainable AI (XAI)
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Elijah Oluwatoyosi Abolaji and Oladayo Tosin Akinwande. AI powered privacy protection: A survey of current state and future directions. World Journal of Advanced Research and Reviews, 2024, 23(3), 2687-2696. Article DOI: https://doi.org/10.30574/wjarr.2024.23.3.2869