Work

The role of deep learning in ensuring privacy integrity and security: Applications in AI-driven cybersecurity solutions

Year: 2024

Type: article

Abstract: 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.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14865285

Authors: Joseph Nnaemeka Chukwunweike, Moshood Yussuf, Oluwatobiloba Okusi, Temitope Oluwatobi Bakare, Ayokunle J. Abisola

Institution: Western Illinois University

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6949941076

FWCI:

Cites:

Cited by:

Related to: