Machine Learning Approaches In Cyber Security Analytics
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Machine Learning Approaches In Cyber Security Analytics
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Author : Tony Thomas
language : en
Publisher: Springer Nature
Release Date : 2019-12-16
Machine Learning Approaches In Cyber Security Analytics written by Tony Thomas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Computers categories.
This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Security Analytics
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Author : Mehak Khurana
language : en
Publisher: CRC Press
Release Date : 2022-06-24
Security Analytics written by Mehak Khurana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Computers categories.
The book gives a comprehensive overview of security issues in cyber physical systems by examining and analyzing the vulnerabilities. It also brings current understanding of common web vulnerabilities and its analysis while maintaining awareness and knowledge of contemporary standards, practices, procedures and methods of Open Web Application Security Project. This book is a medium to funnel creative energy and develop new skills of hacking and analysis of security and expedites the learning of the basics of investigating crimes, including intrusion from the outside and damaging practices from the inside, how criminals apply across devices, networks, and the internet at large and analysis of security data. Features Helps to develop an understanding of how to acquire, prepare, visualize security data. Unfolds the unventured sides of the cyber security analytics and helps spread awareness of the new technological boons. Focuses on the analysis of latest development, challenges, ways for detection and mitigation of attacks, advanced technologies, and methodologies in this area. Designs analytical models to help detect malicious behaviour. The book provides a complete view of data analytics to the readers which include cyber security issues, analysis, threats, vulnerabilities, novel ideas, analysis of latest techniques and technology, mitigation of threats and attacks along with demonstration of practical applications, and is suitable for a wide-ranging audience from graduates to professionals/practitioners and researchers.
Machine Learning Techniques And Analytics For Cloud Security
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Author : Rajdeep Chakraborty
language : en
Publisher: John Wiley & Sons
Release Date : 2021-11-30
Machine Learning Techniques And Analytics For Cloud Security written by Rajdeep Chakraborty 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 2021-11-30 with Computers categories.
MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.
Machine Learning For Cyber Security
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Author : Preeti Malik
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-12-05
Machine Learning For Cyber Security written by Preeti Malik and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-05 with Business & Economics categories.
This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.
Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection
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Author : Shilpa Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-22
Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection written by Shilpa Mahajan 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 2024-03-22 with Computers categories.
APPLYING ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ANALYTICS AND CYBER THREAT DETECTION Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.
Intelligent Approaches To Cyber Security
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Author : Narendra M Shekokar
language : en
Publisher: CRC Press
Release Date : 2023-10-11
Intelligent Approaches To Cyber Security written by Narendra M Shekokar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-11 with Computers categories.
Intelligent Approach to Cyber Security provides details on the important cyber security threats and its mitigation and the influence of Machine Learning, Deep Learning and Blockchain technologies in the realm of cyber security. Features: Role of Deep Learning and Machine Learning in the Field of Cyber Security Using ML to defend against cyber-attacks Using DL to defend against cyber-attacks Using blockchain to defend against cyber-attacks This reference text will be useful for students and researchers interested and working in future cyber security issues in the light of emerging technology in the cyber world.
Modern Approaches In Iot And Machine Learning For Cyber Security
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2023-12-07
Modern Approaches In Iot And Machine Learning For Cyber Security written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Technology & Engineering categories.
This book examines the cyber risks associated with Internet of Things (IoT) and highlights the cyber security capabilities that IoT platforms must have in order to address those cyber risks effectively. The chapters fuse together deep cyber security expertise with artificial intelligence (AI), machine learning, and advanced analytics tools, which allows readers to evaluate, emulate, outpace, and eliminate threats in real time. The book’s chapters are written by experts of IoT and machine learning to help examine the computer-based crimes of the next decade. They highlight on automated processes for analyzing cyber frauds in the current systems and predict what is on the horizon. This book is applicable for researchers and professionals in cyber security, AI, and IoT.
Cyber Security In Business Analytics
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Author : Gururaj H L
language : en
Publisher: CRC Press
Release Date : 2025-09-30
Cyber Security In Business Analytics written by Gururaj H L and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Computers categories.
There is a growing need for insights and practical experiences in the evolving field of cyber security for business analytics a need addressed by Cyber Security in Business Analytics. Divided into sections covering cyber security basics, artificial intelligence (AI) methods for threat detection, and practical applications in e-commerce and e-banking, the book's team of experts provides valuable insights into securing business data and improving decision-making processes. It covers topics such as data privacy, threat detection, risk assessment, and ethical considerations, catering to both technical and managerial audiences. • Presents real-case scenarios for enhancing understanding of how cyber security principles are applied in diverse organizational settings • Offers advanced technologies such as artificial intelligence methods for cyber threat detection, offering readers • Provides a detailed exploration of howAI can make cybersecurity better by helping detect threats, unusual activities, and predict potential risks • Focuses on the convergence of cyber security and data-driven decision-making and explores how businesses can leverage analytics while safeguarding sensitive information • Includes insights into cutting-edge techniques in the field, such as detailed explorations of various cyber security tools within the context of business analytics Cyber Security in Business Analytics will be useful for scholars, researchers and professionals of computer science and analytics.
Artificial Intelligence And Machine Learning In Cyber Security
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Author : Mark Hayward
language : en
Publisher: Mark Hayward
Release Date : 2025-06-06
Artificial Intelligence And Machine Learning In Cyber Security written by Mark Hayward and has been published by Mark Hayward this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks typically requiring human intelligence. These tasks include understanding language, recognizing patterns, solving problems, and making decisions. AI systems can process vast amounts of data quickly and adapt their responses based on new information, which makes them particularly valuable in monitoring and responding to cyber threats. Machine Learning (ML), a subset of AI, focuses specifically on algorithms that enable computers to learn from data without being explicitly programmed for every specific task. In recent years, AI and ML have gained widespread attention for their potential to dramatically enhance cybersecurity defenses
Deep Learning Approaches To Cloud Security
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Author : Pramod Singh Rathore
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-29
Deep Learning Approaches To Cloud Security written by Pramod Singh Rathore 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 2021-12-29 with Technology & Engineering categories.
DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas