Download or read book Securing the Future Cybersecurity Strategies with AI ML and Generative AI written by Purshotam Singh Yadav and published by JEC PUBLICATION. This book was released on with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: .....

Download or read book Generative AI Security written by Ken Huang and published by Springer Nature. This book was released on with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Implementing Generative AI in Cybersecurity written by Anand Vemula and published by Independently Published. This book was released on 2024-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an era where cyber threats are becoming increasingly sophisticated, "Implementing Generative AI in Cybersecurity: Techniques, Tools, and Case Studies" serves as a comprehensive guide for professionals and enthusiasts looking to leverage the power of generative AI to bolster their cybersecurity defenses. This book delves into the intersection of two rapidly evolving fields-artificial intelligence and cybersecurity-providing readers with the knowledge and tools necessary to stay ahead of cyber adversaries. The book begins with an introduction to generative AI and its pivotal role in transforming cybersecurity. It covers the basics of generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), explaining their mechanics and applications in creating synthetic data, enhancing training datasets, and anonymizing sensitive information. Moving into practical applications, the book explores how generative AI can be used for data augmentation and synthesis to improve the accuracy and robustness of machine learning models used in threat detection and incident response. Readers will learn about the latest techniques for detecting and defending against adversarial attacks, ensuring their AI systems remain resilient against sophisticated manipulations. A significant portion of the book is dedicated to real-world case studies, demonstrating how leading organizations in various sectors-finance, healthcare, and government-have successfully implemented generative AI solutions to enhance their cybersecurity posture. These case studies provide valuable insights into the practical challenges and strategies for integrating AI technologies into existing security frameworks. Deepfake detection and prevention, a crucial aspect of modern cybersecurity, is also covered in depth. The book outlines state-of-the-art detection techniques and countermeasures to combat the rising threat of synthetic media used for malicious purposes. The use of natural language processing (NLP) in security is another focal point, highlighting its applications in phishing detection, secure communication analysis, and threat intelligence. Ethical considerations, privacy concerns, and the regulatory landscape are discussed to provide a holistic view of the challenges and responsibilities involved in deploying AI-driven cybersecurity solutions. "Implementing Generative AI in Cybersecurity: Techniques, Tools, and Case Studies" is an essential resource for cybersecurity professionals, AI practitioners, and anyone interested in the future of digital security, offering practical guidance and actionable insights to navigate the complexities of integrating generative AI into cybersecurity strategies.

Download or read book AI for Cybersecurity written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on 2024-04-06 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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!

Download or read book Artificial Intelligence for Security written by Tuomo Sipola and published by Springer Nature. This book was released on with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Securing Your AI and Machine Learning Systems written by Alexander Polyakov and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Design secure AI/ML solutions About This Video Gain practical experience with various open-source tools such as ART (Adversarial Robustness Toolkit) and DeepSec, developed to test machine learning algorithms for security Learn to design secure AI solutions depending on risks that are typical for your application with the help of a unique approach Understand the attacks and different approaches for securing various AI/ML systems In Detail Artificial Intelligence (AI) is literally eating software as more and more solutions become ML-based. Unfortunately, these systems also have vulnerabilities; but, compared to software security, few people are really knowledgeable about this area. If it's impossible to secure AI against cyberattacks, there will be no AI-based technologies, such as self-driving cars, and yet another "AI winter" will soon be on us. This course is almost certainly the first public, online, hands-on introduction to the future perspectives of cybersecurity and adopts a clear and easy-to-follow approach. In this course, you will learn about high-level risks targeting AI/ML systems. You will design specific security tests for image recognition systems and master techniques to test against attacks. You will then learn about various categories of adversarial attacks and how to choose the right defense strategy. By the end of this course, you will be acquainted with various attacks and, more importantly, with the steps that you can take to secure your AI and machine learning systems effectively. For this course, practical experience with Python, machine learning, and deep learning frameworks is assumed, along with some basic math skills.

Download or read book Generative AI Cybersecurity and Ethics written by Mohammad Rubyet Islam and published by Wiley. This book was released on 2025-02-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book AI Enabled Threat Detection and Security Analysis for Industrial IoT written by Hadis Karimipour and published by Springer Nature. This book was released on 2021-08-03 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book THE NEXT FRONTIER IN CYBERSECURITY Integrating AI ML and Generative AI for Advanced Protection written by Dr Sivaraju Kuraku and published by JEC PUBLICATION. This book was released on with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: ......

Download or read book Generative AI and Implications for Ethics Security and Data Management written by Gomathi Sankar, Jeganathan and published by IGI Global. This book was released on 2024-08-21 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.

Download or read book Cyber Security Meets Machine Learning written by Xiaofeng Chen and published by Springer Nature. This book was released on 2021-07-02 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Adversary Aware Learning Techniques and Trends in Cybersecurity written by Prithviraj Dasgupta and published by Springer Nature. This book was released on 2021-01-22 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for effectively addressing vulnerabilities of AI/ML operating in large, distributed environments like Internet of Things (IoT) with diverse data modalities, and, techniques to enable AI/ML systems to intelligently interact with humans that could be malicious adversaries and/or benign teammates. Readers of this book will be equipped with definitive information on recent developments suitable for countering adversarial threats in AI/ML systems towards making them operate in a safe, reliable and seamless manner.

Download or read book Cybersecurity and Artificial Intelligence written by Hamid Jahankhani and published by Springer Nature. This book was released on with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Implications of Artificial Intelligence for Cybersecurity written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-01-27 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The Digital Shield written by Drew Ashton and published by eBookIt.com. This book was released on 2024-08-19 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protect the Digital Frontier with AI In an age where cyber threats lurk behind every corner of the internet, safeguarding our digital assets has never been more critical. "The Digital Shield: AI in Cyber Defense" is an essential read for anyone looking to understand and deploy the revolutionary capabilities of Artificial Intelligence in the field of cybersecurity. Across its insightful chapters, the book explores the early adoption of AI in digital defense and reveals the key drivers that propelled its rise. Readers will gain a comprehensive understanding of cyber threats, from well-known attacks like malware and ransomware to intricate advanced persistent threats (APTs). Delve into the sophisticated techniques of AI applied in safeguarding our digital lives. Discover how machine learning, deep learning, and natural language processing (NLP) contribute to anomaly detection and real-time threat monitoring. The depth and breadth of AI's role–from intrusion detection systems to automated patch management–are illustrated through vivid, real-world case studies. This book doesn't shy away from critical discussions. It challenges you to consider the ethical implications and privacy concerns associated with AI in cybersecurity. What does the future hold? How will legal frameworks evolve to keep pace with technological advancements? The book's exploration of regulatory and legal aspects provides crucial insights into these pressing questions. Enriched with practical examples and success stories, "The Digital Shield: AI in Cyber Defense" not only offers a roadmap for today's cyber defenders but also sheds light on the emerging technologies that will define tomorrow's battles. This indispensable resource will arm you with the knowledge to anticipate and counteract the ever-evolving cyber threats, ensuring that you are always one step ahead in protecting what matters most. Don't wait for a cyber catastrophe to understand the stakes. Equip yourself with the power of AI and be part of the future of cyber defense.

Download or read book Hands On Artificial Intelligence for Cybersecurity written by Alessandro Parisi and published by Packt Publishing Ltd. This book was released on 2019-08-02 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book AI DRIVEN CYBER DEFENSE Enhancing Security with Machine Learning and Generative AI written by Dr Sivaraju Kuraku and published by JEC PUBLICATION. This book was released on with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: ......