Description
Book SynopsisSECURITY TECHNOLOGIES AND SOCIAL IMPLICATIONS Explains how the latest technologies can advance policing and security, identify threats, and defend citizens from crime and terrorism Security Technologies and Social Implications focuses on the development and application of new technologies that police and homeland security officers can leverage as a tool for both predictive and intelligence-led investigations. The book recommends the best practices for incorporation of these technologies into day-to-day activities by law enforcement agencies and counter-terrorism units. Practically, it addresses legal, technological, and organizational challenges (e.g. resource limitation and privacy concerns) combined with challenges related to the adoption of innovative technologies. In contrast to classic tools, modern policing and security requires the development and implementation of new technologies using AI, machine learning, social media tracking, drones, robots, GIS, computer vision, and mo
Table of ContentsThe circle of change: technology impact on LEAs
Data Protection Impact Assessments in Law Enforcement: Identifying and Mitigating Risks in Algorithmic Policing
Methods of Stakeholder Engagement for the Co-Design of Security Technologies
Performance Assessment of Soft biometrics technologies for border crossing
Counter-Unmanned Aerial Vehicle Systems: Technical, Training and Regulatory Challenges
Critical Infrastructure security using Computer Vision Technologies
Evaluation of Content Fusion Algorithms for Large and Heterogeneous Datasets
Stakeholder Engagement Model to facilitate the uptake by end-users of Crisis Communication Systems
CRIME MAPPING IN CRIME ANALYSIS – THE DEVELOPMENTS IN THE PAST TWO DECADES
The Threat of Behavioural Radicalization Online: Conceptual Challenges and Technical Solutions Provided by the PROPHETS (Preventing Radicalization Online through the Proliferation of Harmonized ToolkitS) Project
Blockchain technologies for chain of custody authentication
Chances and challenges of predictive policing for law enforcement agencies
Conclusions
