Application of Big Data for National Security

A Practitioner's Guide to Emerging Technologies

Häftad, Engelska, 2015

AvBabak Akhgar,Gregory B. Saathoff,Hamid R Arabnia,Richard Hill,Andrew Staniforth,Petra Saskia Bayerl,UK) Akhgar, Babak (Professor of Informatics, Sheffield Hallam University, Sheffield,USA) Saathoff, Gregory B. (Associate Professor of Research, University of Virginia,USA) Arabnia, Hamid R (Professor of Computer Science, University of Georgia, Athens, GA,UK) Hill, Richard (Department of Mathematics, University College London,UK) Staniforth, Andrew (Detective Inspector and Senior Research Fellow, CENTRIC, Sheffield Hallam University, Sheffield,Netherlands) Bayerl, Petra Saskia (Visiting Fellow, CENTRIC

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Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue.

The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security

Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention
Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime
Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context
Indicates future directions for Big Data as an enabler of advanced crime prevention and detection

Produktinformation

Utgivningsdatum2015-02-17
Mått191 x 235 x 18 mm
Vikt660 g
FormatHäftad
SpråkEngelska
Antal sidor316
FörlagElsevier Science
ISBN9780128019672

Tillhör följande kategorier

Politisk aktivism inom Samhälle och politik
IT-säkerhet inom Data och IT

Babak Akhgar is Professor of Informatics and Director of CENTRIC (Center of Excellence in Terrorism, Resilience, Intelligence and Organized Crime Research) at Sheffield Hallam University (UK) and Fellow of the British Computer Society. He has more than 100 refereed publications in international journals and conferences on information systems with specific focus on knowledge management (KM). He is member of editorial boards of several international journals and has acted as Chair and Program Committee Member for numerous international conferences. He has extensive and hands-on experience in the development, management and execution of KM projects and large international security initiatives (e.g., the application of social media in crisis management, intelligence-based combating of terrorism and organized crime, gun crime, cyber-crime and cyber terrorism and cross cultural ideology polarization). In addition to this he is the technical lead of two EU Security projects: “Courage on Cyber-Crime and Cyber-Terrorism and “Athena onthe Application of Social Media and Mobile Devices in Crisis Management. He has co-edited several books on Intelligence Management.. His recent books are titled “Strategic Intelligence Management (National Security Imperatives and Information and Communications Technologies), “Knowledge Driven Frameworks for Combating Terrorism and Organised Crime and “Emerging Trends in ICT Security. Prof Akhgar is member of the academic advisory board of SAS UK. Hamid R. Arabnia is currently a Full Professor of Computer Science at University of Georgia where he has been since October 1987. His research interests include Parallel and distributed processing techniques and algorithms, interconnection networks, and applications in Computational Science and Computational Intelligence (in particular, in image processing, medical imaging, bioinformatics, and other computational intensive problems). Dr. Arabnia is Editor-in-Chief of The Journal of is Associate Editor of IEEE Transactions on Information Technology in Biomedicine . He has over 300 publications (journals, proceedings, editorship) in his area of research in addition he has edited two titles Emerging Trends in ICT Security (Elsevier 2013), and Advances in Computational Biology (Springer 2012). Andrew Staniforth, Detective Inspector and Advisory Board Member and Senior Research Fellow, Centre of Excellence in Terrorism, Resilience, Intelligence and Organised Crime Research (CENTRIC).

Section 1: Introduction to Big DataChapter 1 – An Introduction to Big DataChapter 2 – Drilling into the Big Data Goldmine: Data Fusion and High Performance Analytics for Intelligence ProfessionalsSection 2: Core Concepts and Application ScenariosChapter 3 – Harnessing the Power of Big Data to Counter International TerrorismChapter 4 – Big Data and Law Enforcement: Advances, Implications, and Lessons from an Active Shooter Case StudyChapter 5 – Interpretation and Insider Threat: Re-Reading the Anthrax Mailings of 2001 Through a "Big Data" LensChapter 6 – Critical Infrastructure Protection by Harnessing Big DataChapter 7 – Military and Big Data RevolutionChapter 8 – Cyber-Crime, Attack-Motivations and Implications for Big Data and National Security Section 3: Mathods and Technological SolutionsChapter 9 – Requirements and Challenges for Big Data ArchitectureChapter 10 – Tools and Technologies for the Implementation of Big DataChapter 11 – Mining Social Media: Architecture, Tools, and Approaches to Detect Criminal ActivityChapter 12 – Making Sense of Unstructured Natural Language InformationChapter 13 – Literature Mining and Ontology Mapping Applied to Big DataChapter 14 – Big Data Concerns in Autonomous AI SystemsSection 4: Legal and Social ChallengesChapter 15 – The Legal Challenges of Big Data Applications in Law EnforcementChapter 16 – Big Data and the Italian Legal FrameworkChapter 17 – Accounting for Cultural Influences in Big Data AnalyticsChapter 18 – Making Sense of the Noise: An ABC Approach to Big Data and Security