Machine Learning Approaches in Cyber Security Analytics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Machine Learning Approaches in Cyber Security Analytics PDF full book. Access full book title Machine Learning Approaches in Cyber Security Analytics by Tony Thomas. Download full books in PDF and EPUB format.
Author: Tony Thomas Publisher: Springer Nature ISBN: 9811517061 Category : Computers Languages : en Pages : 217
Book Description
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.
Author: Tony Thomas Publisher: Springer Nature ISBN: 9811517061 Category : Computers Languages : en Pages : 217
Book Description
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.
Author: Xiaofeng Chen Publisher: Springer Nature ISBN: 9813367261 Category : Computers Languages : en Pages : 168
Book Description
Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.
Author: Mehak Khurana Publisher: CRC Press ISBN: 1000597563 Category : Computers Languages : en Pages : 286
Book Description
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.
Author: Shilpa Mahajan Publisher: John Wiley & Sons ISBN: 139419644X Category : Computers Languages : en Pages : 373
Book Description
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 Cyber Security 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 Cyber Security 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 Cyber Security 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.
Author: Rajdeep Chakraborty Publisher: John Wiley & Sons ISBN: 1119764092 Category : Computers Languages : en Pages : 484
Book Description
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.
Author: Vinit Kumar Gunjan Publisher: Springer Nature ISBN: 3031099559 Category : Technology & Engineering Languages : en Pages : 415
Book Description
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.
Author: Mamoun Alazab Publisher: Springer ISBN: 3030130576 Category : Computers Languages : en Pages : 246
Book Description
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Author: Rakesh M. Verma Publisher: CRC Press ISBN: 1000727653 Category : Mathematics Languages : en Pages : 357
Book Description
Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.
Author: Ganapathi, Padmavathi Publisher: IGI Global ISBN: 1522596135 Category : Computers Languages : en Pages : 482
Book Description
As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Author: Brij B. Gupta Publisher: CRC Press ISBN: 0429995725 Category : Computers Languages : en Pages : 352
Book Description
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.
Author: Tony Thomas
Author: Tony Thomas
Author: Xiaofeng Chen
Author: Mehak Khurana
Author: Shilpa Mahajan
Author: Rajdeep Chakraborty
Author: Vinit Kumar Gunjan
Author: Mamoun Alazab
Author: Rakesh M. Verma
Author: Ganapathi, Padmavathi
Author: Brij B. Gupta