Reinforcement Learning For Cyber Operations
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Reinforcement Learning For Cyber Operations
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Author : Abdul Rahman
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-22
Reinforcement Learning For Cyber Operations written by Abdul Rahman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.
A comprehensive and up-to-date application of reinforcement learning concepts to offensive and defensive cybersecurity In Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing, a team of distinguished researchers delivers an incisive and practical discussion of reinforcement learning (RL) in cybersecurity that combines intelligence preparation for battle (IPB) concepts with multi-agent techniques. The authors explain how to conduct path analyses within networks, how to use sensor placement to increase the visibility of adversarial tactics and increase cyber defender efficacy, and how to improve your organization's cyber posture with RL and illuminate the most probable adversarial attack paths in your networks. Containing entirely original research, this book outlines findings and real-world scenarios that have been modeled and tested against custom generated networks, simulated networks, and data. You'll also find: A thorough introduction to modeling actions within post-exploitation cybersecurity events, including Markov Decision Processes employing warm-up phases and penalty scaling Comprehensive explorations of penetration testing automation, including how RL is trained and tested over a standard attack graph construct Practical discussions of both red and blue team objectives in their efforts to exploit and defend networks, respectively Complete treatment of how reinforcement learning can be applied to real-world cybersecurity operational scenarios Perfect for practitioners working in cybersecurity, including cyber defenders and planners, network administrators, and information security professionals, Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing will also benefit computer science researchers.
Eccws 2021 20th European Conference On Cyber Warfare And Security
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Author : Dr Thaddeus Eze
language : en
Publisher: Academic Conferences Inter Ltd
Release Date : 2021-06-24
Eccws 2021 20th European Conference On Cyber Warfare And Security written by Dr Thaddeus Eze and has been published by Academic Conferences Inter Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-24 with History categories.
Conferences Proceedings of 20th European Conference on Cyber Warfare and Security
Challenges And Solutions For Cybersecurity And Adversarial Machine Learning
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Author : Ul Rehman, Shafiq
language : en
Publisher: IGI Global
Release Date : 2025-06-06
Challenges And Solutions For Cybersecurity And Adversarial Machine Learning written by Ul Rehman, Shafiq and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
Adversarial machine learning poses a threat to cybersecurity by exploiting vulnerabilities in AI models through manipulated inputs. These attacks can cause systems in healthcare, finance, and autonomous vehicles to make dangerous or misleading decisions. A major challenge lies in detecting these small issues and defending learning models and organizational data without sacrificing performance. Ongoing research and cross-sector collaboration are essential to develop robust, ethical, and secure machine learning systems. Further research may reveal better solutions to converge cyber technology, security, and machine learning tools. Challenges and Solutions for Cybersecurity and Adversarial Machine Learning explores adversarial machine learning and deep learning within cybersecurity. It examines foundational knowledge, highlights vulnerabilities and threats, and proposes cutting-edge solutions to counteract adversarial attacks on AI systems. This book covers topics such as data privacy, federated learning, and threat detection, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and data scientists.
Machine Learning Optimization And Data Science
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Author : Giuseppe Nicosia
language : en
Publisher: Springer Nature
Release Date : 2025-03-03
Machine Learning Optimization And Data Science written by Giuseppe Nicosia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-03 with Computers categories.
The three-volume set LNAI 15508-15510 constitutes the refereed proceedings of the 10th International Conference on Machine Learning, Optimization, and Data Science, LOD 2024, held in Castiglione della Pescaia, Italy, during September 22–25, 2024. This year, in the LOD Proceedings decided to also include the papers of the fourth edition of the Symposium on Artificial Intelligence and Neuroscience (ACAIN 2024). The 79 full papers included in this book were carefully reviewed and selected from 127 submissions. The LOD 2024 proceedings focus on machine learning, deep learning, AI, computational optimization, neuroscience and big data that includes invited talks, tutorial talks, special sessions, industrial tracks, demonstrations and oral and poster presentations of refereed papers.
Information Systems Security
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Author : Somanath Tripathy
language : en
Publisher: Springer Nature
Release Date : 2021-12-14
Information Systems Security written by Somanath Tripathy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-14 with Computers categories.
This book constitutes the proceedings of the 17th International Conference on Information Systems Security, ICISS 2021, held in Patna, India, during December 16-20, 2021. The 9 regular papers, 2 short papers and 4 work-in-progress papers included in this volume were carefully reviewed and selected from a total of 48 submissions. The papers were organized in topical sections named: attack detection, malware identification, data security in distributed systems, and applied cryptography.
Machine Learning For Computer And Cyber Security
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Author : Brij B. Gupta
language : en
Publisher: CRC Press
Release Date : 2019-02-05
Machine Learning For Computer And Cyber Security written by Brij B. Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-05 with Computers categories.
While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques. This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals. Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.
Network Science And Cybersecurity
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Author : Robinson E. Pino
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-14
Network Science And Cybersecurity written by Robinson E. Pino and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-14 with Computers categories.
Network Science and Cybersecurity introduces new research and development efforts for cybersecurity solutions and applications taking place within various U.S. Government Departments of Defense, industry and academic laboratories. This book examines new algorithms and tools, technology platforms and reconfigurable technologies for cybersecurity systems. Anomaly-based intrusion detection systems (IDS) are explored as a key component of any general network intrusion detection service, complementing signature-based IDS components by attempting to identify novel attacks. These attacks may not yet be known or have well-developed signatures. Methods are also suggested to simplify the construction of metrics in such a manner that they retain their ability to effectively cluster data, while simultaneously easing human interpretation of outliers. This is a professional book for practitioners or government employees working in cybersecurity, and can also be used as a reference. Advanced-level students in computer science or electrical engineering studying security will also find this book useful .
Iccws 2021 16th International Conference On Cyber Warfare And Security
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Author : Dr Juan Lopez Jr
language : en
Publisher: Academic Conferences Limited
Release Date : 2021-02-25
Iccws 2021 16th International Conference On Cyber Warfare And Security written by Dr Juan Lopez Jr and has been published by Academic Conferences Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-25 with History categories.
These proceedings represent the work of contributors to the 16th International Conference on Cyber Warfare and Security (ICCWS 2021), hosted by joint collaboration of Tennessee Tech Cybersecurity Education, Research and Outreach Center (CEROC), Computer Science department and the Oak Ridge National Laboratory, Tennessee on 25-26 February 2021. The Conference Co-Chairs are Dr. Juan Lopez Jr, Oak Ridge National Laboratory, Tennessee, and Dr. Ambareen Siraj, Tennessee Tech’s Cybersecurity Education, Research and Outreach Center (CEROC), and the Program Chair is Dr. Kalyan Perumalla, from Oak Ridge National Laboratory, Tennessee.
Deep Learning Innovations For Securing Critical Infrastructures
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Author : Kumar, Rajeev
language : en
Publisher: IGI Global
Release Date : 2025-04-18
Deep Learning Innovations For Securing Critical Infrastructures written by Kumar, Rajeev and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-18 with Computers categories.
Deep learning innovations play a crucial role in securing critical infrastructures, offering advanced solutions to protect vital systems from sophisticated cyber threats. By leveraging neural networks and advanced algorithms, deep learning enables real-time anomaly detection, pattern recognition, and predictive threat analysis, which are essential for safeguarding critical sectors such as energy, transportation, healthcare, and finance. These technologies can identify vulnerabilities, respond to breaches, and adapt to new attacks, providing a strong defense against cyber risks. As the digital landscape becomes more interconnected, the integration of deep learning into cybersecurity strategies will enhance resilience while ensuring the safe operation of essential services. Deep Learning Innovations for Securing Critical Infrastructures explores the cutting-edge integration of neural networks and artificial intelligence (AI) in modern cybersecurity systems. It examines how AI, particularly neural network models, is revolutionizing cybersecurity by automating threat detection, analyzing complex data patterns, and implementing proactive defense mechanisms. This book covers topics such as blockchain, cloud computing, and event management, and is a useful resource for business owners, computer engineers, data scientists, academicians, and researchers.
Machine Learning For Cyber Agents
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Author : Stanislav Abaimov
language : en
Publisher: Springer Nature
Release Date : 2022-01-27
Machine Learning For Cyber Agents written by Stanislav Abaimov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-27 with Computers categories.
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention.