1 Automation and Process Contol Engineer, Gist Limited, United Kingdom.
2 Department of Economics and Decision sciences, Western Illinois University, Macomb, Illinois.
3 IT & Cyber Security Analyst, Bristol Waste Company, Bristol, United Kingdom.
4 Robotics and Automation Engineer, United Kingdom
5 Machine Learning and AI Specialist, United Kingdom.
Research Article
World Journal of Advanced Research and Reviews, 2024, 23(02), 1778-1790
Received on 13 July 2024; revised on 21 August 2024; accepted on 23 August 2024
This article explores the critical role of deep learning in developing AI-driven cybersecurity solutions, with a particular focus on privacy integrity and information security. It investigates how deep neural networks (DNNs) and advanced machine learning techniques are being used to detect and neutralize cyber threats in real time. The article also considers the implications of these technologies for data privacy, discussing the potential risks and benefits of using AI to protect sensitive information. By examining case studies and current research, the piece provides insights into how organizations can deploy deep learning models to enhance both security and privacy integrity in a digital world.
Deep Learning; Cybersecurity; Privacy Preservation; Differential Privacy; Federated Learning; Generative Adversarial Networks (GANs)
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Joseph Nnaemeka Chukwunweike, Moshood Yussuf, Oluwatobiloba Okusi, Temitope Oluwatobi Bakare and Ayokunle J. Abisola. The role of deep learning in ensuring privacy integrity and security: Applications in AI-driven cybersecurity solutions. World Journal of Advanced Research and Reviews, 2024, 23(2), 1778-1790. Article DOI: https://doi.org/10.30574/wjarr.2024.23.2.2550