Explainable AI Within the Digital Transformation and Cyber Physical Systems


Book Description

This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.




Explainable AI for Cybersecurity


Book Description

This book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems.




Explainable Artificial Intelligence for Cyber Security


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.




Implications of Artificial Intelligence for Cybersecurity


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.




Artificial Intelligence Paradigms for Smart Cyber-Physical Systems


Book Description

"This book focuses upon the recent advances in the realization of Artificial Intelligence-based approaches towards affecting secure Cyber-Physical Systems. It features contributions pertaining to this multidisciplinary paradigm, in particular, in its application to building sustainable space by investigating state-of-art research issues, applications and achievements in the field of Computational Intelligence Paradigms for Cyber-Physical Systems"--




Interpretable Machine Learning


Book Description

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.







AI for Cybersecurity


Book Description

Conquer Cybersecurity Challenges with AI: Your Ultimate Guide In today's ever-connected world, cyber threats loom large. Traditional security methods struggle to keep pace with the sophistication and speed of modern attacks. But there's a new weapon in the fight for digital defense: Artificial Intelligence (AI). This comprehensive guide explores how AI is revolutionizing cybersecurity, empowering businesses and individuals to build a more secure future. Demystifying AI for Cybersecurity: Unveiling the magic behind the curtain, this guide dives into the world of AI and machine learning (ML). We'll explain how AI algorithms analyze vast amounts of data, identify patterns, and predict potential attacks, acting as a vigilant guardian on your digital watchtower. AI's Arsenal of Defensive Tools: From proactive threat detection and prevention to swift incident response and forensics, discover how AI empowers your security team. Explore how AI can identify vulnerabilities before attackers exploit them, analyze network traffic for suspicious activity, and automate the analysis of security alerts, saving valuable time and resources. AI Outmaneuvering Phishing Attacks: Phishing scams remain a persistent threat. This guide unveils how AI thwarts these attempts with deception and advanced detection. Learn about honeypots that lure attackers away from real systems, and AI-powered simulations that train employees to identify phishing tactics. Discover how AI analyzes email content and user behavior to flag suspicious attempts before they cause harm. Understanding User Behavior with UEBA: Imagine a guardian angel monitoring your network for unusual activity. UEBA (User and Entity Behavior Analytics) is just that. This guide explores how AI analyzes user and entity behavior to identify potential insider threats or compromised accounts. Learn how UEBA establishes baselines for normal activity and flags anomalies that might indicate a security breach. Securing the Cloud with AI's Power: The cloud offers flexibility and scalability, but security concerns remain. This guide delves into how AI safeguards cloud-based infrastructure and data. Discover how AI continuously monitors cloud workloads, detects threats in real-time, and automates certain security responses, minimizing the impact of incidents. Beyond the Technology: The Human Element While AI offers immense potential, human expertise remains irreplaceable. This guide emphasizes the importance of collaboration between humans and AI. Explore how security professionals leverage AI insights to make critical decisions and ensure ethical considerations are addressed throughout the cybersecurity process. The Future of AI and Cybersecurity: A Collaborative Journey The cybersecurity landscape is constantly evolving, and AI is at the forefront of this transformation. This guide explores the exciting possibilities and ongoing challenges that lie ahead, including AI's ability to adapt to emerging threats and the potential for automated incident response. Embrace a Secure Future with AI: This guide empowers you to understand AI's role in cybersecurity. By leveraging this powerful technology responsibly, you can build a more robust defense against cyber threats. Take the first step towards a more secure digital future – explore the power of AI in cybersecurity today!




Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance


Book Description

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.




AI and Deep Learning in Biometric Security


Book Description

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.