Preventing Data Leakage Using Artificial Intelligence and Neural Networks

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.

Authors

Publication Details

Published
2025-10-29
DOI
https://doi.org/10.38124/ijisrt/25oct328
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Preventing Data Leakage Using Artificial Intelligence and Neural Networks

Jamachi Bernard Udokporo
Information and Cyber Security
article

Preventing Data Leakage Using Artificial Intelligence and Neural Networks

Jamachi Bernard Udokporo
article en

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.

Openalex Percentile: Top 55%
Information and Cyber Security
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