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AI-Based Cybersecurity Threat Detection and Prevention

AI-Based Cybersecurity Threat Detection and Prevention
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Author(s): Tina Sharma (Chandigarh University, India)and Pankaj Sharma (TrueBlue Headquarters, USA)
Copyright: 2024
Pages: 18
Source title: Perspectives on Artificial Intelligence in Times of Turbulence: Theoretical Background to Applications
Source Author(s)/Editor(s): Nuno Geada (ISCTE, University Institute of Lisboa, Portugal)and George Leal Jamil (Informações em Rede C e T Ltda., Brazil)
DOI: 10.4018/978-1-6684-9814-9.ch006

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Abstract

The chapter presents an overview of AI-based cybersecurity threat detection and prevention. It highlights the importance of AI in tackling the ever-increasing threat landscape and explores various techniques and algorithms used in cybersecurity. AI's ability to process real-time data, identify patterns, and provide accurate threat intelligence is emphasized. The chapter covers machine learning, deep learning, and natural language processing, providing practical examples of their application in cybersecurity. Challenges such as data quality and bias are discussed, along with potential solutions. AI-based cybersecurity solutions like intrusion detection systems and threat intelligence platforms are presented. The chapter concludes with a discussion on the future of AI-based cybersecurity, including emerging technologies like quantum computing and blockchain, and the need for ongoing research and development to address evolving threats. Overall, it offers a comprehensive overview of AI's role in cybersecurity, highlighting benefits, challenges, and future directions.

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