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Research Paper | Computer Science and Information Technology | United States of America | Volume 10 Issue 6, June 2021 | Rating: 2.7 / 10
AI-based Systems Enhance Cybersecurity Defenses, Identify and Mitigate Cyber Threats in Real-Time
Rajesh Palthya
Abstract: Artificial intelligence and its subdomain machine learning help to system development by learning from prior data, making logical decisions, and detecting patterns with little to no human intervention. Cybersecurity approaches provide current ways to protect against attacks and dangers. Due to attackers? capacity to escape conventional security solutions, past and traditional security methods are unable to address today?s security concerns. Cybersecurity protects data and software from assaults on servers, computers, smart devices, and networks. There are two key considerations to consider when combining cybersecurity and artificial intelligence (AI). The first is evaluating cybersecurity for circumstances where AI is applied, and the second is employing AI to strengthen cybersecurity measures. With the rapid expansion of digital technologies, cybersecurity threats have become increasingly sophisticated and pervasive. Traditional security measures are often insufficient to detect and respond to these evolving threats. This paper explores the development and implementation of AI-based systems designed to enhance cybersecurity defenses by identifying and mitigating cyber threats in real-time. By leveraging machine learning (ML) and deep learning (DL) techniques, AI systems can analyze vast amounts of data, detect anomalies, and respond to threats faster than traditional methods. This study reviews the current state of AI in cybersecurity, examines case studies of successful implementations, and discusses the challenges and future directions for AI-driven cybersecurity solutions.
Keywords: Artificial Intelligence, Cybersecurity, Threat Detection, Real-Time Mitigation, Machine Learning, Deep Learning
Edition: Volume 10 Issue 6, June 2021
Pages: 1859 - 1864