Artificial Intelligence In Cyber Security Theories And Applications
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| Author | : Tushar Bhardwaj |
| Publisher | : Springer Nature |
| Total Pages | : 144 |
| Release | : 2023-11-10 |
| Genre | : Technology & Engineering |
| ISBN | : 3031285816 |
This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity. The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 99 |
| Release | : 2020-01-27 |
| Genre | : Computers |
| ISBN | : 0309494508 |
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 | : Sucar, L. Enrique |
| Publisher | : IGI Global |
| Total Pages | : 444 |
| Release | : 2011-10-31 |
| Genre | : Computers |
| ISBN | : 160960167X |
One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.
| Author | : Charles A. Kamhoua |
| Publisher | : John Wiley & Sons |
| Total Pages | : 546 |
| Release | : 2021-09-08 |
| Genre | : Technology & Engineering |
| ISBN | : 1119723949 |
GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
| Author | : Haruna Chiroma |
| Publisher | : Springer Nature |
| Total Pages | : 316 |
| Release | : 2021-04-01 |
| Genre | : Technology & Engineering |
| ISBN | : 3030662888 |
This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.
| Author | : Yaokumah, Winfred |
| Publisher | : IGI Global |
| Total Pages | : 302 |
| Release | : 2020-04-10 |
| Genre | : Computers |
| ISBN | : 1799831507 |
In today’s globalized world, businesses and governments rely heavily on technology for storing and protecting essential information and data. Despite the benefits that computing systems offer, there remains an assortment of issues and challenges in maintaining the integrity and confidentiality of these databases. As professionals become more dependent cyberspace, there is a need for research on modern strategies and concepts for improving the security and safety of these technologies. Modern Theories and Practices for Cyber Ethics and Security Compliance is a collection of innovative research on the concepts, models, issues, challenges, innovations, and mitigation strategies needed to improve cyber protection. While highlighting topics including database governance, cryptography, and intrusion detection, this book provides guidelines for the protection, safety, and security of business data and national infrastructure from cyber-attacks. It is ideally designed for security analysts, law enforcement, researchers, legal practitioners, policymakers, business professionals, governments, strategists, educators, and students seeking current research on combative solutions for cyber threats and attacks.
| Author | : Alessandro Parisi |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 331 |
| Release | : 2019-08-02 |
| Genre | : Computers |
| ISBN | : 1789805171 |
Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key FeaturesIdentify and predict security threats using artificial intelligenceDevelop intelligent systems that can detect unusual and suspicious patterns and attacksLearn how to test the effectiveness of your AI cybersecurity algorithms and toolsBook Description Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI. What you will learnDetect email threats such as spamming and phishing using AICategorize APT, zero-days, and polymorphic malware samplesOvercome antivirus limits in threat detectionPredict network intrusions and detect anomalies with machine learningVerify the strength of biometric authentication procedures with deep learningEvaluate cybersecurity strategies and learn how you can improve themWho this book is for If you’re a cybersecurity professional or ethical hacker who wants to build intelligent systems using the power of machine learning and AI, you’ll find this book useful. Familiarity with cybersecurity concepts and knowledge of Python programming is essential to get the most out of this book.
| Author | : El Bachir Boukherouaa |
| Publisher | : International Monetary Fund |
| Total Pages | : 35 |
| Release | : 2021-10-22 |
| Genre | : Business & Economics |
| ISBN | : 1589063953 |
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
| Author | : Khosrow-Pour D.B.A., Mehdi |
| Publisher | : IGI Global |
| Total Pages | : 1162 |
| Release | : 2020-02-01 |
| Genre | : True Crime |
| ISBN | : 1522597166 |
As society continues to rely heavily on technological tools for facilitating business, e-commerce, banking, and communication, among other applications, there has been a significant rise in criminals seeking to exploit these tools for their nefarious gain. Countries all over the world are seeing substantial increases in identity theft and cyberattacks, as well as illicit transactions, including drug trafficking and human trafficking, being made through the dark web internet. Sex offenders and murderers explore unconventional methods of finding and contacting their victims through Facebook, Instagram, popular dating sites, etc., while pedophiles rely on these channels to obtain information and photographs of children, which are shared on hidden community sites. As criminals continue to harness technological advancements that are outpacing legal and ethical standards, law enforcement and government officials are faced with the challenge of devising new and alternative strategies to identify and apprehend criminals to preserve the safety of society. The Encyclopedia of Criminal Activities and the Deep Web is a three-volume set that includes comprehensive articles covering multidisciplinary research and expert insights provided by hundreds of leading researchers from 30 countries including the United States, the United Kingdom, Australia, New Zealand, Germany, Finland, South Korea, Malaysia, and more. This comprehensive encyclopedia provides the most diverse findings and new methodologies for monitoring and regulating the use of online tools as well as hidden areas of the internet, including the deep and dark web. Highlighting a wide range of topics such as cyberbullying, online hate speech, and hacktivism, this book will offer strategies for the prediction and prevention of online criminal activity and examine methods for safeguarding internet users and their data from being tracked or stalked. Due to the techniques and extensive knowledge discussed in this publication it is an invaluable addition for academic and corporate libraries as well as a critical resource for policy makers, law enforcement officials, forensic scientists, criminologists, sociologists, victim advocates, cybersecurity analysts, lawmakers, government officials, industry professionals, academicians, researchers, and students within this field of study.
| Author | : Leslie F. Sikos |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2018-09-27 |
| Genre | : Technology & Engineering |
| ISBN | : 9783319988412 |
This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.
