Threat From The Deep

Since 1950, the South has undergone the most dramatic political transformation of any region in the United States. The once Solid-meaning Democratic-South is now overwhelmingly Republican, and long-disenfranchised African Americans vote at levels comparable to those of whites. In The Rational Southerner, M.V. Hood III, Quentin Kidd, and Irwin L. Morris argue that local strategic dynamics played a decisive and underappreciated role in both the development of the Southern Republican Party and the mobilization of the region's black electorate. Mobilized blacks who supported the Democratic Party made it increasingly difficult for conservative whites to maintain control of the Party's machinery. Also, as local Republican Party organizations became politically viable, the strategic opportunities that such a change provided made the GOP an increasingly attractive alternative for white conservatives. Blacks also found new opportunities within the Democratic Party as whites fled to the GOP, especially in the deep South, where large black populations had the potential to dominate state and local Democratic Parties. As a result, Republican Party viability also led to black mobilization. Using the theory of relative advantage, Hood, Kidd, and Morris provide a new perspective on party system transformation. Following a theoretically-informed description of recent partisan dynamics in the South, they demonstrate, with decades of state-level, sub-state, and individual-level data, that GOP organizational strength and black electoral mobilization were the primary determinants of political change in the region. The authors' finding that race was, and still is, the primary driver behind political change in the region stands in stark contrast to recent scholarship which points to in-migration, economic growth, or religious factors as the locus of transition. The Rational Southerner contributes not only to the study of Southern politics, but to our understanding of party system change, racial politics, and the role that state and local political dynamics play in the larger context of national politics and policymaking.

There is much public concern about threats to global biodiversity, for example from pollution and from climate change, resulting from build-up of greenhouse gases in the atmosphere. This book addresses these concerns by detailing some of the research currently in progress.

A world-class hero confronts ancient "supernatural" evils in an adventure that spans entire planets and defies everyday notions of reality! Still mourning the losses of his beloved Penny Priddy and his surrogate father Professor Hikita, Buckaroo Banzai must also contend with the constant threat of attack from his immortal nemesis Hanoi Xan, ruthless leader of the World Crime League. To make matters worse, Planet 10 warrior queen John Emdall has sent her Lectroid legions against Earth with a brutal ultimatum. Or is her true target Buckaroo Banzai? As the apocalyptic threats continue to mount, only Buckaroo and his Hong Kong Cavaliers stand in the way of global destruction. The long-awaited sequel to The Adventures of Buckaroo Banzai Across the 8th Dimension is finally here after more than 35 years! As told by the Reno Kid to Buckaroo Banzai chronicler E.M. Rauch, this tale follows everyone's favorite scientist-surgeon-entertainer-daredevil as he sets off on a brand-new hair-raising adventure!

Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.

In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include: • Big data analytics for cyber threat intelligence and detection • Artificial intelligence analytics techniques • Real-time situational awareness • Machine learning techniques for CTI • Deep learning techniques for CTI • Malware detection and prevention techniques • Intrusion and cybersecurity threat detection and analysis • Blockchain and machine learning techniques for CTI

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.

Threat intelligence is a surprisingly complex topic that goes far beyond the obvious technical challenges of collecting, modelling and sharing technical indicators. Most books in this area focus mainly on technical measures to harden a system based on threat intel data and limit their scope to single organizations only. This book provides a unique angle on the topic of national cyber threat intelligence and security information sharing. It also provides a clear view on ongoing works in research laboratories world-wide in order to address current security concerns at national level. It allows practitioners to learn about upcoming trends, researchers to share current results, and decision makers to prepare for future developments.

This book is designed for those who want a better grasp of the nature and existential threat of today’s information wars. It uses a conceptual approach to explain the relevant concepts as well as the structural challenges and responsibilities with which policy makers struggle and practitioners must work.