Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities PDF Download

Author: Sanjay Misra
Publisher: Springer Nature
ISBN: 3030722368
Category : Technology & Engineering
Languages : en
Pages : 467

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Book Description
This book provides stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation results (using several analytics tools), and an application-oriented approach that can be demonstrated with respect to data analytics using artificial intelligence to make systems stronger (i.e., impossible to breach). We can see many serious cyber breaches on Government databases or public profiles at online social networking in the recent decade. Today artificial intelligence or machine learning is redefining every aspect of cyber security. From improving organizations’ ability to anticipate and thwart breaches, protecting the proliferating number of threat surfaces with Zero Trust Security frameworks to making passwords obsolete, AI and machine learning are essential to securing the perimeters of any business. The book is useful for researchers, academics, industry players, data engineers, data scientists, governmental organizations, and non-governmental organizations.

Author: Mark Stamp
Publisher: Springer Nature
ISBN: 3030970876
Category : Computers
Languages : en
Pages : 388

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Book Description
This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.

Author: Mohiuddin Ahmed
Publisher: Springer Nature
ISBN: 3030966305
Category : Computers
Languages : en
Pages : 283

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Book Description
This book presents that explainable artificial intelligence (XAI) is going to replace the traditional artificial, machine learning, deep learning algorithms which work as a black box as of today. To understand the algorithms better and interpret the complex networks of these algorithms, XAI plays a vital role. In last few decades, we have embraced AI in our daily life to solve a plethora of problems, one of the notable problems is cyber security. In coming years, the traditional AI algorithms are not able to address the zero-day cyber attacks, and hence, to capitalize on the AI algorithms, it is absolutely important to focus more on XAI. Hence, this book serves as an excellent reference for those who are working in cyber security and artificial intelligence.

Author: Hadis Karimipour
Publisher: Springer Nature
ISBN: 3030766136
Category : Computers
Languages : en
Pages : 250

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Book Description
This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.

Author: Shilpa Mahajan
Publisher: John Wiley & Sons
ISBN: 139419644X
Category : Computers
Languages : en
Pages : 373

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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: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309494508
Category : Computers
Languages : en
Pages : 99

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Book Description
In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.

Author: Om Prakash, Jena
Publisher: IGI Global
ISBN: 166843993X
Category : Computers
Languages : en
Pages : 286

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Book Description
Cyber security is a key focus in the modern world as more private information is stored and saved online. In order to ensure vital information is protected from various cyber threats, it is essential to develop a thorough understanding of technologies that can address cyber security challenges. Artificial intelligence has been recognized as an important technology that can be employed successfully in the cyber security sector. Due to this, further study on the potential uses of artificial intelligence is required. Methods, Implementation, and Application of Cyber Security Intelligence and Analytics discusses critical artificial intelligence technologies that are utilized in cyber security and considers various cyber security issues and their optimal solutions supported by artificial intelligence. Covering a range of topics such as malware, smart grid, data breachers, and machine learning, this major reference work is ideal for security analysts, cyber security specialists, data analysts, security professionals, computer scientists, government officials, researchers, scholars, academicians, practitioners, instructors, and students.

Author: Tuomo Sipola
Publisher: Springer Nature
ISBN: 3031150309
Category : Computers
Languages : en
Pages : 300

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Book Description
This book discusses artificial intelligence (AI) and cybersecurity from multiple points of view. The diverse chapters reveal modern trends and challenges related to the use of artificial intelligence when considering privacy, cyber-attacks and defense as well as applications from malware detection to radio signal intelligence. The chapters are contributed by an international team of renown researchers and professionals in the field of AI and cybersecurity. During the last few decades the rise of modern AI solutions that surpass humans in specific tasks has occurred. Moreover, these new technologies provide new methods of automating cybersecurity tasks. In addition to the privacy, ethics and cybersecurity concerns, the readers learn several new cutting edge applications of AI technologies. Researchers working in AI and cybersecurity as well as advanced level students studying computer science and electrical engineering with a focus on AI and Cybersecurity will find this book useful as a reference. Professionals working within these related fields will also want to purchase this book as a reference.

Author: Hamid Jahankhani
Publisher: Springer Nature
ISBN: 3031522729
Category :
Languages : en
Pages : 329

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Book Description

Author: Xiaofeng Chen
Publisher: Springer Nature
ISBN: 9813367261
Category : Computers
Languages : en
Pages : 168

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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.