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5 books on AI for Cyber Security [PDF]
Updated: May 19, 2024 | 25 |
Books on AI for Cybersecurity serve as indispensable guides for startups venturing into the complex and ever-evolving realm of digital security. These books provide in-depth knowledge about machine learning algorithms, neural networks, and advanced data analytics crucial for detecting and mitigating cyber threats in real-time. By delving into these texts, entrepreneurs can gain a profound understanding of malware analysis, anomaly detection, and threat intelligence, which are pivotal in developing robust AI-powered cybersecurity solutions. Additionally, these resources often delve into ethical hacking techniques and strategies employed by cybercriminals, offering startups invaluable insights into the mindsets and methodologies of adversaries.
1. Artificial Intelligence for Cybersecurity
2022 by Mark Stamp, Corrado Aaron Visaggio, Francesco Mercaldo, Fabio Di Troia
"This book delves into the innovative applications of machine learning, deep learning, and artificial intelligence in the realm of cybersecurity, going beyond mere data application to address intricate challenges at the intersection of deep learning and cybersecurity. It offers valuable insights into the complex 'how' and 'why' questions that emerge in AI's role in security. Topics covered include 'explainable AI,' 'adversarial learning,' 'resilient AI,' and a broad spectrum of related subjects, transcending specific cybersecurity domains from malware to biometrics and more. Designed for researchers, advanced students, and practitioners in the fields of cybersecurity and artificial intelligence, this book serves as an indispensable reference, offering cutting-edge insights and solutions."
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2. AI and Machine Learning for Network and Security Management
2022 by Yulei Wu, Jingguo Ge, Tong Li
"This book comprehensively addresses various critical aspects of network automation in the context of network and security management, encompassing resource allocation, scheduling, network planning, routing, encrypted traffic classification, anomaly detection, and security operations. The authors also introduce their expansive intelligent network management and operation system, elucidating how these components can be seamlessly integrated into the system and the ensuing benefits for network services. Within this insightful work, the authors delve into topics such as leveraging cognitive techniques like knowledge transfer for enhanced network and security management, the applicability of advanced AI and machine learning methods in facilitating network automation, and the broader spectrum of network and security management tasks to which these techniques can be applied. This book serves as a valuable resource for network engineers, content service providers, and cybersecurity specialists seeking to make informed decisions in their respective domains. Additionally, students pursuing related academic disciplines will find this work valuable as it provides a foundational understanding of historical knowledge while highlighting recent advancements in the field."
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3. AI-Enabled Threat Detection and Security Analysis for Industrial IoT
2021 by Hadis Karimipour, Farnaz Derakhshan
"This book presents cutting-edge insights into security and privacy challenges within cyber-physical systems (CPS) and the industrial Internet of Things (IIoT), exploring how Artificial Intelligence (AI) and Machine Learning (ML) can effectively tackle these issues. It offers a range of defense strategies, including intelligent cyber-attack and anomaly detection algorithms tailored to various IIoT applications. Chapters cover essential aspects such as AI integration in IIoT environments, data security, privacy concerns, and the application of blockchain technology. Advanced topics delve into AI-based anomaly detection methods, including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning, and multi-stage learning. Aimed at researchers and professionals in computer security, this book also serves as a valuable reference for advanced students in computer science, cyber security, electrical engineering, and system engineering."
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4. Artificial Intelligence in Cyber Security: Impact and Implications: Security Challenges, Technical and Ethical Issues, Forensic Investigative Challenges
2021 by Reza Montasari, Hamid Jahankhani
"This book serves as a valuable resource for experts in the fields of cybersecurity, digital forensics, and network security. In recent times, artificial intelligence (AI) has garnered significant attention from researchers in both academic and industrial sectors, resulting in a rapid and remarkable enhancement of AI capabilities. Often regarded as the Fourth Industrial Revolution, AI represents a pivotal technological shift following the advancements in mobile and cloud computing. AI holds the potential to enrich various aspects of our lives, offering a wide array of advantageous applications across diverse sectors. However, alongside its myriad benefits, AI presents a confluence of legal, ethical, security, and privacy challenges, exacerbated by its exploitation by malicious actors. These challenges jeopardize privacy and security at national, organizational, and individual levels. Consequently, this book aims to confront and mitigate some of these challenges, emphasizing the implications, impact, and potential solutions to these issues."
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5. Machine Learning for Cybersecurity Cookbook: Over 80 recipes on how to implement machine learning algorithms for building security systems using Python
2019 by Emmanuel Tsukerman
"This book equips organizations with essential cybersecurity techniques to combat evolving threats, using Python libraries like TensorFlow and scikit-learn to implement cutting-edge AI methods. It provides a comprehensive guide to setting up a secure lab environment and walks readers through the implementation of key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book covers building classifiers and features for malware, handling cybersecurity tasks like identifying malicious URLs, spam email detection, intrusion detection, network protection, and user and process behavior tracking. Additionally, it explores advanced security applications like generative adversarial networks (GANs) and autoencoders and addresses secure and private AI for safeguarding consumer privacy in ML models."
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Artificial Intelligence for Cybersecurity
2022 by Mark Stamp, Corrado Aaron Visaggio, Francesco Mercaldo, Fabio Di Troia
"This book delves into the innovative applications of machine learning, deep learning, and artificial intelligence in the realm of cybersecurity, going beyond mere data application to address intricate challenges at the intersection of deep learning and cybersecurity. It offers valuable insights into the complex 'how' and 'why' questions that emerge in AI's role in security. Topics covered include 'explainable AI,' 'adversarial learning,' 'resilient AI,' and a broad spectrum of related subjects, transcending specific cybersecurity domains from malware to biometrics and more. Designed for researchers, advanced students, and practitioners in the fields of cybersecurity and artificial intelligence, this book serves as an indispensable reference, offering cutting-edge insights and solutions."
Download PDF
2. AI and Machine Learning for Network and Security Management
2022 by Yulei Wu, Jingguo Ge, Tong Li
"This book comprehensively addresses various critical aspects of network automation in the context of network and security management, encompassing resource allocation, scheduling, network planning, routing, encrypted traffic classification, anomaly detection, and security operations. The authors also introduce their expansive intelligent network management and operation system, elucidating how these components can be seamlessly integrated into the system and the ensuing benefits for network services. Within this insightful work, the authors delve into topics such as leveraging cognitive techniques like knowledge transfer for enhanced network and security management, the applicability of advanced AI and machine learning methods in facilitating network automation, and the broader spectrum of network and security management tasks to which these techniques can be applied. This book serves as a valuable resource for network engineers, content service providers, and cybersecurity specialists seeking to make informed decisions in their respective domains. Additionally, students pursuing related academic disciplines will find this work valuable as it provides a foundational understanding of historical knowledge while highlighting recent advancements in the field."
Download PDF
3. AI-Enabled Threat Detection and Security Analysis for Industrial IoT
2021 by Hadis Karimipour, Farnaz Derakhshan
"This book presents cutting-edge insights into security and privacy challenges within cyber-physical systems (CPS) and the industrial Internet of Things (IIoT), exploring how Artificial Intelligence (AI) and Machine Learning (ML) can effectively tackle these issues. It offers a range of defense strategies, including intelligent cyber-attack and anomaly detection algorithms tailored to various IIoT applications. Chapters cover essential aspects such as AI integration in IIoT environments, data security, privacy concerns, and the application of blockchain technology. Advanced topics delve into AI-based anomaly detection methods, including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning, and multi-stage learning. Aimed at researchers and professionals in computer security, this book also serves as a valuable reference for advanced students in computer science, cyber security, electrical engineering, and system engineering."
Download PDF
4. Artificial Intelligence in Cyber Security: Impact and Implications: Security Challenges, Technical and Ethical Issues, Forensic Investigative Challenges
2021 by Reza Montasari, Hamid Jahankhani
"This book serves as a valuable resource for experts in the fields of cybersecurity, digital forensics, and network security. In recent times, artificial intelligence (AI) has garnered significant attention from researchers in both academic and industrial sectors, resulting in a rapid and remarkable enhancement of AI capabilities. Often regarded as the Fourth Industrial Revolution, AI represents a pivotal technological shift following the advancements in mobile and cloud computing. AI holds the potential to enrich various aspects of our lives, offering a wide array of advantageous applications across diverse sectors. However, alongside its myriad benefits, AI presents a confluence of legal, ethical, security, and privacy challenges, exacerbated by its exploitation by malicious actors. These challenges jeopardize privacy and security at national, organizational, and individual levels. Consequently, this book aims to confront and mitigate some of these challenges, emphasizing the implications, impact, and potential solutions to these issues."
Download PDF
5. Machine Learning for Cybersecurity Cookbook: Over 80 recipes on how to implement machine learning algorithms for building security systems using Python
2019 by Emmanuel Tsukerman
"This book equips organizations with essential cybersecurity techniques to combat evolving threats, using Python libraries like TensorFlow and scikit-learn to implement cutting-edge AI methods. It provides a comprehensive guide to setting up a secure lab environment and walks readers through the implementation of key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book covers building classifiers and features for malware, handling cybersecurity tasks like identifying malicious URLs, spam email detection, intrusion detection, network protection, and user and process behavior tracking. Additionally, it explores advanced security applications like generative adversarial networks (GANs) and autoencoders and addresses secure and private AI for safeguarding consumer privacy in ML models."
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
