Authors : Jamachi Bernard Udokporo

Volume/Issue : Volume 10 - 2025, Issue 10 - October

Google Scholar : https://tinyurl.com/2nb3a27y

Scribd : https://tinyurl.com/yz7rben9

DOI : https://doi.org/10.38124/ijisrt/25oct328

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Abstract : As cybersecurity threats continue to escalate in a data-driven world, AI and neural networks offer a promising solution for preventing data leakage. Organisations across various sectors increasingly rely on data to drive innovation, make informed decisions, and remain competitive. However, this reliance also exposes them to the risk of data breaches or leakage, which can result in severe financial losses, legal ramifications, and long-term reputational damage. Therefore, this research paper aims to explore the applications of Artificial Intelligence (AI) and Neural Networks for enhancing Data Loss Prevention (DLP) mechanisms. This project has the potential to transform data security practices. As organisations become increasingly concerned about data leakage, traditional approaches such as endpoint-based protection are proving inadequate against emerging cyber threats. AI and Neural Networks offer a cost-effective solution, dynamically learning and adapting to detect high-profile sensitive information patterns. This work could enhance data security, reduce operational costs, and better prepare organisations for the evolving threat landscape.

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