Cyber Security Solutions For Protecting And Building The Future Smart Grid
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Cyber Security Solutions for Protecting and Building the Future Smart Grid
Cyber Security Solutions for Protecting and Building the Future Smart Grid guides the reader from the fundamentals of grid security to practical techniques necessary for grid defense. Through its triple structure, readers can expect pragmatic, detailed recommendations on the design of solutions and real-world problems. The book begins with a supportive grounding in the security needs and challenges of renewable-integrated modern grids. Next, industry professionals provide a wide range of case studies and examples for practical implementation.Finally, cutting-edge researchers and industry practitioners guide readers through regulatory requirements and develop a clear framework for identifying best practices. Providing a unique blend of theory and practice, this comprehensive resource will help readers safeguard the sustainable grids of the future. - Provides a fundamental overview of the challenges facing the renewable-integrated electric grid - Offers a wide range of case studies, examples, and practical techniques for implementing security in smart and micro-grids - Includes detailed guidance and discussion of international standards and regulations for industry and implementation
Advances in Intelligent Systems and Digital Applications
This book serves as a comprehensive reference, providing cutting-edge knowledge on intelligent systems and digital applications. It covers theoretical foundations and significant issues in machine learning, deep learning, and data analytics. Each chapter concludes with a detailed bibliography for further in-depth reading.Divided into two sections—Foundations and Applications—the book offers a complete source of information on its theme. The chapters include concepts, algorithms, figures, graphs, and tables to enhance readability. The target audience includes researchers, practitioners, and postgraduate and graduate students developing or utilizing artificial intelligence algorithms in various applications.
Improving Threat Detection, Network Security, and Incident Response With AI
Artificial intelligence (AI) strengthens cybersecurity by enhancing threat detection, fortifying network security, and streamlining incident response. Traditional security systems often struggle to manage modern cyber threats. AI addresses this challenge by analyzing data in real-time, identifying patterns and anomalies that may indicate malicious activity. Machine learning algorithms detect attacks and threats faster than humans, allowing organizations to respond proactively. In network security, AI helps in monitoring traffic, predicting vulnerabilities, and automatically implementing protective measures. AI-driven incident response tools assess the breaches, contain threats, and initiate recovery protocols. As cyber threats evolve, integrating AI into security infrastructure is essential for maintaining resilience in the digital age. Improving Threat Detection, Network Security, and Incident Response With AI explores the role of AI in cybersecurity, focusing on its applications in threat detection, malware analysis, network security, and incident response. It examines key AI techniques such as machine learning, deep learning, and natural language processing (NLP) that are transforming cybersecurity operations. This book covers topics such as robotics, software engineering, and behavioral analysis, and is a useful resource for computer engineers, security professionals, academicians, researchers, and data scientists.