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Utilizing generative AI for cyber de...
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Jhanjhi, Noor Zaman.
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Utilizing generative AI for cyber defense strategies
Record Type:
Electronic resources : Monograph/item
Title/Author:
Utilizing generative AI for cyber defense strategies/ Noor Zaman Jhanjhi.
remainder title:
Utilizing generative artificial intelligence for cyber defense strategies
Author:
Jhanjhi, Noor Zaman.
Published:
Hershey, Pennsylvania :IGI Global, : 2025.,
Description:
1 online resource (xix, 525 p.) :ill.
[NT 15003449]:
Preface -- Chapter 1. Federated Learning for Collaborative Cyber Defense -- Chapter 2. Risk Assessment and Mitigation With Generative AI Models -- Chapter 3. Dynamic Defense Strategies With Generative AI -- Chapter 4. Unleashing thePower of Generative Adversarial Networks for Cybersecurity: Proactive Defense and Innovation -- Chapter 5. Enhancing Security Through Generative AI-Based Authentication -- Chapter 6. Generative AI for Threat Intelligence and Information Sharing -- Chapter 7. Generative AI for Threat Hunting and Behaviour Analysis -- Chapter 8. A Methodical Approach to Exploiting Vulnerabilities and Countermeasures Using AI -- Chapter 9. Variational Autoencoders (VAEs) for Anomaly Detection --Chapter 10. A Novel Approach for Intrusion Detection System Using Deep Learning Architecture -- Chapter 11. A New Approach for Detecting Malware Using a Convolutional Autoencoder With Kernel Density Estimation -- Chapter 12. Scouting the Juncture of Internet of Things (IoT), Deep Learning, and Cybercrime: Powering Legal Perspectives on Advanced Data Analytics -- Chapter 13. Muscles of Deep Learning (DL) and Internet of Things (IoT) in Cyber Crimes Investigation: Legal Dimensions in Space-Age Data Analytics -- Chapter 14. Safeguarding the Future: Advancements in Cybersecurity via Generative AI -- Compilation of References -- About the Contributors -- Index.
Subject:
Artificial intelligence. -
Online resource:
https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8944-7
ISBN:
9798369389461
Utilizing generative AI for cyber defense strategies
Jhanjhi, Noor Zaman.
Utilizing generative AI for cyber defense strategies
[electronic resource] /Utilizing generative artificial intelligence for cyber defense strategiesNoor Zaman Jhanjhi. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (xix, 525 p.) :ill. - Advances in digital crime, forensics, and cyber terrorism (ADCFCT) book series. - Advances in digital crime, forensics, and cyber terrorism (ADCFCT) book series..
Includes bibliographical references and index.
Preface -- Chapter 1. Federated Learning for Collaborative Cyber Defense -- Chapter 2. Risk Assessment and Mitigation With Generative AI Models -- Chapter 3. Dynamic Defense Strategies With Generative AI -- Chapter 4. Unleashing thePower of Generative Adversarial Networks for Cybersecurity: Proactive Defense and Innovation -- Chapter 5. Enhancing Security Through Generative AI-Based Authentication -- Chapter 6. Generative AI for Threat Intelligence and Information Sharing -- Chapter 7. Generative AI for Threat Hunting and Behaviour Analysis -- Chapter 8. A Methodical Approach to Exploiting Vulnerabilities and Countermeasures Using AI -- Chapter 9. Variational Autoencoders (VAEs) for Anomaly Detection --Chapter 10. A Novel Approach for Intrusion Detection System Using Deep Learning Architecture -- Chapter 11. A New Approach for Detecting Malware Using a Convolutional Autoencoder With Kernel Density Estimation -- Chapter 12. Scouting the Juncture of Internet of Things (IoT), Deep Learning, and Cybercrime: Powering Legal Perspectives on Advanced Data Analytics -- Chapter 13. Muscles of Deep Learning (DL) and Internet of Things (IoT) in Cyber Crimes Investigation: Legal Dimensions in Space-Age Data Analytics -- Chapter 14. Safeguarding the Future: Advancements in Cybersecurity via Generative AI -- Compilation of References -- About the Contributors -- Index.
"As cyber threats become increasingly sophisticated, the need for innovative defense strategies becomes urgent. Generative artificial intelligence (AI) offers a revolutionary approach to enhance cybersecurity. By utilizing advanced algorithms, data analysis, and machine learning, generative AI can simulate complex attack scenarios, identify vulnerabilities, and develop proactive defense mechanisms while adapting to modern-day cyber-attacks. AI strengthens current organizational security while offering quick, effective responses to emerging threats. Decisive strategies are needed to integrate generative AI into businesses defense strategies and protect organizations from attacks, secure digital data, andensure safe business processes. Utilizing Generative AI for Cyber Defense Strategies explores the utilization of generative AI tools in organizational cyber security and defense. Strategies for effective threat detection and mitigation arepresented, with an emphasis on deep learning, artificial intelligence, and Internet of Things (IoT) technology. This book covers topics such as cyber security, threat intelligence, and behavior analysis, and is a useful resource for computerengineers, security professionals, business owners, government officials, data analysts, academicians, scientists, and researchers."--
Mode of access: World Wide Web.
ISBN: 9798369389461Subjects--Topical Terms:
516317
Artificial intelligence.
Subjects--Index Terms:
Anomaly Detection.Index Terms--Genre/Form:
542853
Electronic books.
LC Class. No.: QA76.9.A25 / J43 2024eb
Dewey Class. No.: 005.8
Utilizing generative AI for cyber defense strategies
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Preface -- Chapter 1. Federated Learning for Collaborative Cyber Defense -- Chapter 2. Risk Assessment and Mitigation With Generative AI Models -- Chapter 3. Dynamic Defense Strategies With Generative AI -- Chapter 4. Unleashing thePower of Generative Adversarial Networks for Cybersecurity: Proactive Defense and Innovation -- Chapter 5. Enhancing Security Through Generative AI-Based Authentication -- Chapter 6. Generative AI for Threat Intelligence and Information Sharing -- Chapter 7. Generative AI for Threat Hunting and Behaviour Analysis -- Chapter 8. A Methodical Approach to Exploiting Vulnerabilities and Countermeasures Using AI -- Chapter 9. Variational Autoencoders (VAEs) for Anomaly Detection --Chapter 10. A Novel Approach for Intrusion Detection System Using Deep Learning Architecture -- Chapter 11. A New Approach for Detecting Malware Using a Convolutional Autoencoder With Kernel Density Estimation -- Chapter 12. Scouting the Juncture of Internet of Things (IoT), Deep Learning, and Cybercrime: Powering Legal Perspectives on Advanced Data Analytics -- Chapter 13. Muscles of Deep Learning (DL) and Internet of Things (IoT) in Cyber Crimes Investigation: Legal Dimensions in Space-Age Data Analytics -- Chapter 14. Safeguarding the Future: Advancements in Cybersecurity via Generative AI -- Compilation of References -- About the Contributors -- Index.
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"As cyber threats become increasingly sophisticated, the need for innovative defense strategies becomes urgent. Generative artificial intelligence (AI) offers a revolutionary approach to enhance cybersecurity. By utilizing advanced algorithms, data analysis, and machine learning, generative AI can simulate complex attack scenarios, identify vulnerabilities, and develop proactive defense mechanisms while adapting to modern-day cyber-attacks. AI strengthens current organizational security while offering quick, effective responses to emerging threats. Decisive strategies are needed to integrate generative AI into businesses defense strategies and protect organizations from attacks, secure digital data, andensure safe business processes. Utilizing Generative AI for Cyber Defense Strategies explores the utilization of generative AI tools in organizational cyber security and defense. Strategies for effective threat detection and mitigation arepresented, with an emphasis on deep learning, artificial intelligence, and Internet of Things (IoT) technology. This book covers topics such as cyber security, threat intelligence, and behavior analysis, and is a useful resource for computerengineers, security professionals, business owners, government officials, data analysts, academicians, scientists, and researchers."--
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https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8944-7
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