Amiya Nayak – författare
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2 produkter
2 produkter
Handbook of Applied Algorithms
Solving Scientific, Engineering, and Practical Problems
Inbunden, Engelska, 2008
1 631 kr
Skickas inom 5-8 vardagar
Discover the benefits of applying algorithms to solve scientific, engineering, and practical problems Providing a combination of theory, algorithms, and simulations, Handbook of Applied Algorithms presents an all-encompassing treatment of applying algorithms and discrete mathematics to practical problems in "hot" application areas, such as computational biology, computational chemistry, wireless networks, and computer vision. In eighteen self-contained chapters, this timely book explores:* Localized algorithms that can be used in topology control for wireless ad-hoc or sensor networks* Bioinformatics algorithms for analyzing data* Clustering algorithms and identification of association rules in data mining* Applications of combinatorial algorithms and graph theory in chemistry and molecular biology* Optimizing the frequency planning of a GSM network using evolutionary algorithms* Algorithmic solutions and advances achieved through game theory Complete with exercises for readers to measure their comprehension of the material presented, Handbook of Applied Algorithms is a much-needed resource for researchers, practitioners, and students within computer science, life science, and engineering. Amiya Nayak, PhD, has over seventeen years of industrial experience and is Full Professor at the School of Information Technology and Engineering at the University of Ottawa, Canada. He is on the editorial board of several journals. Dr. Nayak's research interests are in the areas of fault tolerance, distributed systems/algorithms, and mobile ad-hoc networks. Ivan StojmenoviC?, PhD, is Professor at the University of Ottawa, Canada (www.site.uottawa.ca/~ivan), and Chair Professor of Applied Computing at the University of Birmingham, United Kingdom. Dr. Stojmenovic? received the Royal Society Wolfson Research Merit Award. His current research interests are mostly in the design and analysis of algorithms for wireless ad-hoc and sensor networks.
978 kr
Kommande
This book provides a comprehensive guide to integrating Artificial Intelligence (AI), Large Language Models (LLMs), and quantum-safe security mechanisms into modern cybersecurity practices. It begins by examining the evolving cyber threat landscape and the growing need for intelligent, adaptive defense mechanisms. Also, the role of AI, LLMs, and quantum computing in cybersecurity, outlining the book’s objectives and structure are introduced. The fundamentals of LLM architectures and training methodologies are explored, followed by their practical applications in threat detection, malware analysis, phishing prevention, and automated incident response.Practical integration of LLMs into cybersecurity frameworks is discussed, including enhancements to intrusion detection systems, security information, Event Management (SIEM) platforms, and real-time threat intelligence. Real-world case studies highlight successful deployments. This book also addresses key challenges such as interpretability, scalability, ethical concerns, bias, and adversarial vulnerabilities, offering mitigation strategies and best practices. The quantum computing section examines threats to classical cryptography and presents quantum-safe solutions, including post-quantum cryptography and Quantum Key Distribution (QKD). The convergence of AI and quantum-safe security is explored, showing how LLMs can support quantum-resilient defenses.This book is designed for cybersecurity professionals, researchers, and policymakers seeking effective strategies to secure increasingly complex digital environments. Advanced-level students majoring in computer science and/or ML/DL engineering will also find this book useful as a reference.