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"This book provides the latest empirical research and theoretical frameworks in the area of information security, presenting research on developing sufficient security measures for new environments by discussing challenges faced by researchers as well as unconventional solutions to these problems"--Provided by publisher.
Computers at Risk presents a comprehensive agenda for developing nationwide policies and practices for computer security. Specific recommendations are provided for industry and for government agencies engaged in computer security activities. The volume also outlines problems and opportunities in computer security research, recommends ways to improve the research infrastructure, and suggests topics for investigators. The book explores the diversity of the field, the need to engineer countermeasures based on speculation of what experts think computer attackers may do next, why the technology community has failed to respond to the need for enhanced security systems, how innovators could be encouraged to bring more options to the marketplace, and balancing the importance of security against the right of privacy.
In the rapidly evolving digital landscape, the importance of cybersecurity has never been more critical. With the increasing sophistication of cyber threats, traditional security measures often fall short in providing adequate protection. Cyber artificial intelligence (AI) offers advanced capabilities to detect, prevent, and respond to attacks in real time. As cyber threats continue to grow in complexity and frequency, the integration of AI into cybersecurity frameworks is not just advantageous but essential for maintaining robust and resilient defenses. Redefining Security With Cyber AI delves into the profound transformation of security paradigms brought about by the advent of AI. This book explores the intricate dance between the ever-expanding frontiers of digital technology and the AI-driven mechanisms that aim to safeguard them. Covering topics such as artificial neural networks, intrusion detection, and large language models, this book is an excellent resource for cybersecurity professionals, AI and machine learning researchers, IT executives and managers, policy makers and regulators, postgraduate students and educators, academicians, and more.
In this fast-paced global economy, academia and industry must innovate to evolve and succeed. Today’s researchers and industry experts are seeking transformative technologies to meet the challenges of tomorrow. Cutting-edge technological advances in cybersecurity solutions aid in enabling the security of complex heterogeneous high-performance computing (HPC) environments. On the other hand, HPC facilitates powerful and intelligent innovative models for reducing time to response to identify and resolve a multitude of potential, newly emerging cyberattacks. Cybersecurity and High-Performance Computing Environments provides a collection of the current and emergent research innovations, practices, and applications focusing on the interdependence of cybersecurity and HPC domains for discovering and resolving new emerging cyber-threats. KEY FEATURES Represents a substantial research contribution to the state-of-the-art solutions for addressing the threats to confidentiality, integrity, and availability (CIA triad) in HPC environments Covers the groundbreaking and emergent solutions that utilize the power of the HPC environments to study and understand the emergent, multifaceted, anomalous, and malicious characteristics The content will help university students, researchers, and professionals understand how HPC research fits broader cybersecurity objectives and vice versa.
The longstanding practice of keeping academic disciplines separate has been a barrier to effectively addressing the complex challenges in our world. The boundaries separating fields like healthcare, social sciences, and technology have obscured the potential for interdisciplinary collaboration, preventing us from unlocking innovative solutions to the most pressing issues of our time. As a result, the critical problems we face, from healthcare inequities to technological advancements with ethical dilemmas, have remained largely unresolved. This fragmented approach to academic inquiry has left a void in our quest to tackle these challenges effectively. The solution is found within the pages of Innovations, Securities, and Case Studies Across Healthcare, Business, and Technology. This groundbreaking compendium illuminates the transformative potential of interdisciplinary collaboration, offering direction and support in the form of knowledge for scholars, researchers, practitioners, and students committed to solving real-world problems. By harnessing the collective wisdom of diverse disciplines, the book demonstrates how convergence across healthcare, social sciences, organizational behavior, and technology can lead to groundbreaking insights and solutions. It showcases success stories and innovative strategies that drive positive change within our societies, offering a roadmap towards a brighter, more interconnected future.
Technological tools have enhanced the available opportunities and activities in the realm of e-business. In organizations that support real-time business-critical operations, the proper use and maintenance of relevant technology is crucial. Maximizing Information System Availability Through Bayesian Belief Network Approaches: Emerging Research and Opportunities is a pivotal book that features the latest research perspectives on the implementation of effective information systems in business contexts. Highlighting relevant topics such as data security, investment viability, and operational risk management, this book is ideally designed for managers, professionals, academics, practitioners, and students interested in novel techniques for maintaining and measuring information system availability.
Large Language Models (LLMs) are redefining the landscape of cybersecurity, offering innovative methods for detecting software vulnerabilities. By applying advanced AI techniques to identify and predict weaknesses in software code, including zero-day exploits and complex malware, LLMs provide a proactive approach to securing digital environments. This integration of AI and cybersecurity presents new possibilities for enhancing software security measures. Application of Large Language Models (LLMs) for Software Vulnerability Detection offers a comprehensive exploration of this groundbreaking field. These chapters are designed to bridge the gap between AI research and practical application in cybersecurity, in order to provide valuable insights for researchers, AI specialists, software developers, and industry professionals. Through real-world examples and actionable strategies, the publication will drive innovation in vulnerability detection and set new standards for leveraging AI in cybersecurity.
Data analysis forms the basis of many modes of research ranging from scientific discoveries to governmental findings. With the advent of machine intelligence and neural networks, extracting and modeling, approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other. Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities provides emerging information on extraction and prediction patterns in data mining along with knowledge discovery. While highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes. This book is a vital resource for researchers, academics, and those seeking new information on data mining techniques and trends.
Cloud computing has quickly become the next big step in security development for companies and institutions all over the world. With the technology changing so rapidly, it is important that businesses carefully consider the available advancements and opportunities before implementing cloud computing in their organizations. The Handbook of Research on Security Considerations in Cloud Computing brings together discussion on current approaches to cloud-based technologies and assesses the possibilities for future advancements in this field. Highlighting the need for consumers to understand the unique nature of cloud-delivered security and to evaluate the different aspects of this service to verify if it will meet their needs, this book is an essential reference source for researchers, scholars, postgraduate students, and developers of cloud security systems.
The recent explosion in complex global networking architectures has spurred a concomitant rise in the need for robust information security. Further, as computing power increases exponentially with every passing year, so do the number of proposed cryptographic schemata for improving and ensuring the encryption integrity of cutting-edge infosec protocols. Improving Information Security Practices through Computational Intelligence presents an overview of the latest and greatest research in the field, touching on such topics as cryptology, stream ciphers, and intrusion detection, and providing new insights to an audience of students, teachers, and entry-level researchers working in computational intelligence, information security, and security engineering.