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E-raamat: Security Technologies and Social Implications [Wiley Online]

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  • Formaat: 352 pages
  • Ilmumisaeg: 04-Oct-2022
  • Kirjastus: Wiley-IEEE Press
  • ISBN-10: 1119834171
  • ISBN-13: 9781119834175
Teised raamatud teemal:
  • Wiley Online
  • Hind: 178,68 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
Security Technologies and Social ImplicationsSuurem pilt
  • Formaat: 352 pages
  • Ilmumisaeg: 04-Oct-2022
  • Kirjastus: Wiley-IEEE Press
  • ISBN-10: 1119834171
  • ISBN-13: 9781119834175
Teised raamatud teemal:
Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119834175
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 more. As crime in general and cybercrime in particular, become more and more sophisticated, security requires a complex mix of social measures which include prevention, detection, investigation and prosecution. Effective solutions to this problem require continuous synergy and innovation from different scientific fields and their incorporation into the day-to-day practice of law enforcement agencies (LEAs). The use of technologies by LEAs is mandated in two different ways: - use of legacy technologies and novel platforms specifically dedicated for LEA applications (which we will refer to as professional LEA technology platforms) - technologies introduced for other (e.g. consumer) applications but which can be utilised by LEAs enabling new ways of activities (which we will refer to as consumer technologies). Law enforcement agencies need to understand technologies available, uses and limitations, and ethical, regulatory or legal issues.-- B>SECURITY 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 more. As crime (and cybercrime in particular) becomes more and more sophisticated, security requires a complex mix of social measures, including prevention, detection, investigation, and prosecution. Key topics related to these developments and their implementations covered in Security Technologies and Social Implications include: New security technologies and how these technologies can be implemented in practice, plus associated social, ethical or policy issues Expertise and commentary from individuals developing and testing new technologies and individuals using the technologies within their everyday roles The latest advancements in commercial and professional law enforcement technologies and platforms Commentary on how technologies can advance humanity by making policing and security more efficient and keeping citizens safe Security Technologies and Social Implications serves as a comprehensive resource for defense personnel and law enforcement staff, practical security engineers, and trainee staff in security and police colleges to understand the latest security technologies, with a critical look at their uses and limitations regarding potential ethical, regulatory, or legal issues.
List of Contributors
xii
Preface xv
Introduction xvii
1 The Circle of Change: Technology Impact on LEAs
1(31)
Ines Sucic
1.1 Introduction
1(2)
1.2 Study Aims and Objectives
3(1)
1.3 Methodology
3(1)
1.4 Results
4(13)
1.4.1 Study Characteristics
4(1)
1.4.2 Diverse Technologies Adoption
5(3)
1.4.3 Real-Time Data Providers
8(2)
1.4.4 Predictive Policing
10(2)
1.4.5 Smart Borders
12(1)
1.4.6 Communication Between Police and Citizens
13(4)
1.5 Discussion
17(2)
1.6 Instead of Conclusion
19(1)
1.A Appendix
20(12)
References
26(6)
2 Data Protection Impact Assessments in Law Enforcement: Identifying and Mitigating Risks in Algorithmic Policing
32(29)
Thomas Marquenie
Katherine Quezada-Tavarez
2.1 Introduction
32(1)
2.2 Legal Framework and Guidance
33(5)
2.2.1 The DPIA Requirement
33(2)
2.2.2 Elements of a DPIA
35(1)
2.2.3 State of the Art of DPIA Guidance and Methodology for Law Enforcement
36(2)
2.3 Importance and Role of DPIAs in Law Enforcement
38(3)
2.3.1 Significance of DPIAs
38(1)
2.3.2 Illustrative Case Law - Bridges v. South Wales Police
39(2)
2.4 Key Legal and Ethical Risks in Algorithmic Policing
41(5)
2.4.1 Fundamental Rights
41(2)
2.4.2 Unfairness and Opacity
43(1)
2.4.3 Police Integrity
44(2)
2.5 Best Practices: Mitigation Measures and Safeguards
46(7)
2.5.1 Access Control and Information Security
47(2)
2.5.2 Value-Sensitive Design
49(2)
2.5.3 Human Oversight
51(2)
2.6 Conclusion
53(8)
References
54(7)
3 Methods of Stakeholder Engagement for the Co-Design of Security Technologies
61(21)
Andrea lannone
Luigi Briguglio
Carmela Occhipinti
Valeria Cesaroni
3.1 Toward a Holistic Approach for Technology Assessment
61(4)
3.2 Methods of Stakeholder Engagement
65(13)
3.2.1 Stakeholder Identification and Mapping
65(2)
3.2.2 Stakeholder Engagement and Co-Design
67(3)
3.2.3 Sentiment Analysis
70(4)
3.2.4 Focus Groups
74(4)
3.3 Conclusions
78(1)
3.4 Recommendations
79(3)
References
80(2)
4 Performance Assessment of Soft Biometrics Technologies for Border Crossing
82(40)
Bilal Hassan
Ebroul Izquierdo
Krishna Chandramouli
4.1 Introduction
82(3)
4.2 Literature Review
85(4)
4.3 Human Body Anthropometrics
89(5)
4.3.1 Human Body Keypoints Estimation
90(1)
4.3.2 Anthropometric Features Estimation Using Landmark Localization Tools
90(1)
4.3.2.1 OpenPose for Anthropometric Features Estimation
91(1)
4.3.2.2 AlphaPose for Anthropometric Features Estimation
92(2)
4.4 Working on Dataset for Soft Biometrics
94(3)
4.4.1 Front-View Gait Dataset
94(1)
4.4.2 MMV Pedestrian Dataset
95(2)
4.5 Some Influential Factors for Soft Biometrics
97(2)
4.6 Working with Limited Data Using Transfer Learning
99(4)
4.6.1 Transfer Learning for Feature Extraction and Classification
100(1)
4.6.2 Initial Outcome of Transfer Learning-Based Feature Estimation and Classification
101(2)
4.7 Experimental Result
103(8)
4.8 Discussion
111(3)
4.9 Conclusion
114(8)
References
115(7)
5 Counter-Unmanned Aerial Vehicle Systems: Technical Training, and Regulatory Challenges
122(27)
David Fortune
Hotger Nitsch
Garik Markarian
Damir Ostermanm
Andrew Staniforth
5.1 Introduction
122(1)
5.2 Drone Terror Threat Landscape
123(4)
5.3 UAV Configurations and Categories of UAVs
127(3)
5.4 Counter-Drone Technology
130(5)
5.5 Programming Rogue Drone Countermeasures
135(3)
5.5.1 The Counter-UAV Neutralization Chain
136(2)
5.6 Training End Users of C-UAV Systems
138(8)
5.7 Conclusions
146(3)
References
147(2)
6 Critical Infrastructure Security Using Computer Vision Technologies
149(32)
Xindi Zhang
Ebroul Izquierdo
Krishna Chandramouli
6.1 Introduction
149(3)
6.2 Literature Review
152(2)
6.3 Critical Infrastructure Security Using Computer Vision Technologies
154(11)
6.3.1 Framework for Detecting Drone Intruders
154(2)
6.3.1.1 System Configuration for the Region of Protection
156(1)
6.3.1.2 Situation Awareness Module
157(1)
6.3.1.3 PTZ Platform Signalling and Control
158(3)
6.3.1.4 Multi-Class Drone Classification using Deep-Learning
161(1)
6.3.1.5 Tracking Interface with Sensing Equipment
162(2)
6.3.1.6 Alert Component
164(1)
6.4 Intelligent Situational Awareness Framework for Intruder Detection
165(5)
6.4.1 Temporal Smoothing
166(1)
6.4.2 Encrypted Media Repository
166(1)
6.4.3 Privacy-Preserving Technologies
166(1)
6.4.4 Knowledge Model
167(1)
6.4.5 Threat Evaluator
168(1)
6.4.6 Command Center
169(1)
6.5 Experimental Result
170(5)
6.5.1 Drone Detection Accuracy
171(1)
6.5.2 Tracking Accuracy
171(1)
6.5.3 Intruder Detection Capability
172(1)
6.5.4 System Detection and Tracking Performance
173(2)
6.5.5 Evaluation of System Latency Against Geographical Perimeter
175(1)
6.6 Distance Estimation
175(2)
6.7 Conclusion
177(4)
References
177(4)
7 Evaluation of Content Fusion Algorithms for Large and Heterogeneous Datasets
181(17)
Theodoras Alexakis
Nikolaos Peppes
Evgenia Adamopoulou
Konstantinos Demestichas
Konstantina Remoundou
7.1 Introduction
181(1)
7.2 Data Preprocessing and Similarity Calculation Techniques
182(2)
7.3 Description of the Algorithms Used
184(3)
7.3.1 Jaro Similarity and Distance
184(1)
7.3.2 Jaro-Winkler Similarity and Distance
185(1)
7.3.3 Levenshtein Distance and Similarity
185(1)
7.3.4 Cosine Similarity
186(1)
7.3.5 Jaccard Similarity
187(1)
7.4 Proposed Methodology and Data Used
187(2)
7.5 Results
189(3)
7.6 Person Fusion Toolset Design for Future Development
192(2)
7.7 Discussion
194(4)
References
196(2)
8 Stakeholder Engagement Model to Facilitate the Uptake by End Users of Crisis Communication Systems
198(24)
Grigore M. Havdrneanu
Laura Petersen
Natasha McCrone
8.1 Introduction
198(2)
8.2 Risk and Crisis Communication Challenges for CBRNe
200(2)
8.3 CBRNe Disaster Crisis Communication Systems, Especially Disaster Apps
202(1)
8.4 The PROACTIVE Stakeholder Engagement Model
203(13)
8.4.1 Two Advisory Boards: PSAB and CSAB
203(1)
8.4.1.1 The Practitioner Stakeholder Advisory Board (PSAB)
203(1)
8.4.1.2 The Civil Society Advisory Board (CSAB)
204(1)
8.4.2 Recruitment for the Advisory Boards
205(2)
8.4.2.1 Personalized Individual Emails and Follow-Up Process for the CSAB
207(1)
8.4.3 Engaging the Two Advisory Boards
208(1)
8.4.3.1 The Pre-Exercise Workshops
208(1)
8.4.3.2 Mobile App Workshops
209(2)
8.4.3.3 Data Breach Workshop
211(1)
8.4.3.4 Focus Groups with the CSAB
212(1)
8.4.4 Integration of the MoSCoW Findings in the Crisis Communication System
213(2)
8.4.5 Three Field Exercises
215(1)
8.5 Lessons Learnt About the Stakeholder Engagement Model
216(2)
8.5.1 Positive Impact on the Crisis Communication System Development Process
216(1)
8.5.2 Challenges Identified
217(1)
8.5.3 Recommendations
217(1)
8.6 Going Forward: Ensuring the Crisis Communication System's Market Uptake
218(4)
References
219(3)
9 Crime Mapping in Crime Analysis: The Developments in the Past Two Decades
222(25)
Gorazd MeSko
Katja Eman
Rok Hacin
9.1 Introduction
222(4)
9.2 Introducing Crime Mapping to the Slovenian Police
226(2)
9.3 Crime Mapping Studies
228(7)
9.3.1 Crime Mapping in Slovenia Before 2000
229(2)
9.3.2 Crime Mapping in Slovenia After 2000
231(4)
9.4 Geographic Information Systems Laboratory - "GIS Lab" - at the Faculty of Criminal Justice and Security, University of Maribor and Cooperation with the Slovenian Police
235(2)
9.5 First Steps and Inclusion of Crime Analysis to Research and Teaching at the Faculty of Criminal Justice and Security, University of Maribor
237(2)
9.6 Discussion and Conclusion
239(8)
References
241(6)
10 The Threat of Behavioral Radicalizatlon Online: Conceptual Challenges and Technical Solutions Provided by the PROPHETS (Preventing Radlcalization Online through the Proliferation of Harmonized Toolkits) Project
247(15)
Ruta Karlovid
Hotger Nitsch
Sven-Eric Fikenscher
Damir Osterman
Sotirios Menexis
Theodora Tsikrika
Stefanos Vrochidis
Loannis Kompatsiaris
Arif Sahar
10.1 The Growing Threat of Online Radicalization
247(2)
10.2 The Implications of Online Radicalization
249(2)
10.3 Delineating Essential Radicalization-Related Online Activities
251(1)
10.4 The Root Causes of Behavioral Radicalization Online: Identifying the Proper Vulnerability Indicators
252(2)
10.5 PROPHETS Tools: Preventing, Detecting, Investigating, and Studying Behavioral Radicalization Online
254(1)
10.6 Monitoring and Situational Awareness Toolkit
255(1)
10.7 Policymaking Toolkit
256(1)
10.8 Expert Notification Portal
257(1)
10.9 Conclusion: Combining Social Science and Technological Insights
258(4)
References
259(3)
11 Blockchain Technologies for Chain of Custody Authentication
262(28)
Krishna Chandramouli
Roxana Horincar
Charlotte Jacobe de Naurois
Dirk Pallmer
David Faure
Wilmuth Muller
Konstantinos Demestichas
11.1 Introduction
262(4)
11.2 MAGNETO Architecture
266(1)
11.3 Literature Review
266(3)
11.4 Semantic Framework for Recording Evidence Transactions
269(6)
11.5 Evidence Lifecycle Management
275(1)
11.6 IPFS Storage
276(3)
11.7 Accessibility and Evidence Traceability
279(3)
11.8 MAGNETO Features Against Cognitive Biases
282(5)
11.9 Conclusions
287(3)
References
288(2)
12 Chances and Challenges of Predictive Policing for Law Enforcement Agencies
290(24)
Sebastian Allertseder
Guenter Okon
Thomas Schweer
12.1 Next Generation Policing by Prediction of Crime
291(1)
12.2 Lessons Learned from Previous Mistakes
291(3)
12.3 A Question of Methodology
294(1)
12.4 Intuitive Method
294(1)
12.5 Statistical-Nomothetical Prognosis
295(1)
12.6 Clinical-Idiographic Prognosis
296(1)
12.7 Methodology of Criminal Forecasting
296(2)
12.8 Rational Choice Theory
298(1)
12.9 Learning Theories
298(1)
12.10 Routine Activity Approach
299(1)
12.11 The Ecological Approach
300(2)
12.12 The Technological Dimension and Data-Protection Challenges
302(2)
12.13 Predictive Policing in the Field of Radicalization and Terrorism
304(1)
12.14 Personal Risk Assessment in Context of Radicalization - Findings from the PREVISION Project
305(1)
12.15 Personal Risk Assessment
305(2)
12.16 Text Analysis
307(1)
12.17 Identification of Problematic Content
307(1)
12.18 Methodological Design
308(6)
References
310(4)
Index 314
Garik Markarian is an Emeritus Professor of Lancaster University and CEO of Rinicom Ltd (UK).

Rua Karlovic´ is Vice Dean for Research at the Police College in Zagreb, Croatia.

Holger Nitsch is Head of the Research and Social Science Department at the College of the Bavarian Police, Germany

Krishna Chandramouli is Chief Technology Officer at Venaka Media Limited and Subject Matter Expert of AI at CBRNE Ltd.
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