Dr. Reza Montasari is a Senior Lecturer in Cyber Threats at the Hillary Rodham Clinton School of Law in Swansea University. Reza obtained his BSc (Hons) in Multimedia Computing and MSc in Computer Forensics both from the University of South Wales and his PhD in Digital Forensics from the University of Derby. He is a Fellow of Higher Education Academy (FHEA), a Chartered Engineer (CEng), a Member of the Institution of Engineering and Technology (IET), and a Member of the Chartered Society of Forensic Sciences (MCSFS). Reza's main research interests lie in the areas of Digital Forensics, Artificial Intelligence and Cyber Security but also include Cyber Terrorism, Cyber Law and Cyber Criminology. He has authored numerous journal articles, conference papers, book chapters, media articles and recently co-authored an edited volume in his fields of expertise. Reza frequently presents at various conferences including the annual International Conference on Global Security, Safety & Sustainability (ICGS3). He has also given a number of invited talks including his recent presentations at International Conference on Cyberlaw, Cybercrime & Cybersecurity (India, virtual conference) and at the College of Policing and The Investigator Spring National Digital Media Investigator's (DMI) Conference (Oxford, UK., 2019). Reza serves as an Editorial Board Member, a Programme Steering Committee Member and a Reviewer for a number of leading international journals and conferences in the fields of Digital Forensics and Cyber Security. He has previously worked with Cheshire Police Headquarters and South Wales Gwent Police High Tech Crime Units. He is a Member of Strategic Independent Advisory Group at South Wales Police, Wales, U.K. He is also a Guest Writer for Today's Legal Cyber Risk to provide advice on the latest Cyber Security issues. Reza is an experienced supervisor and examiner of undergraduate and postgraduate candidates, and has recently been appointed as an External Examiner to the University of South Wales, Wales, U.K.

Dr. Victoria Carpenter, BSc (UCF), PhD (Hull), has been the Head of Research Development at the University of Bedfordshire since joining the University in November 2018. Victoria started her academic career in 2001 as a Lecturer in Spanish at the University of Derby, later expanding into the area of research and knowledge transfer development. As the Head of Research Development in the Research & Innovation Service, Victoria oversees the work of the Research Graduate School, provides them with academic direction and guidance, coordinates the support for graduate research students, and supports research development.

Victoria is an active researcher specialising in representations of violence in the state and public discourse, relationship between knowledge and emotions, and hegemonic and posthegemonic power distribution mechanisms.

Dr Anthony Masys is an Associate Professor and Director of Global Disaster Management, Humanitarian Assistance and Homeland Security.  A former senior Air Force Officer, Dr Masys has a BSc in Physics and MSc in Underwater Acoustics and Oceanography from the Royal Military College of Canada and a PhD from the University of Leicester. He is Editor in Chief for Springer Publishing book series: Advanced Sciences and Technologies for Security Applications and holds various advisory board positions with academic journals and books series.

Dr Masys is an internationally recognized author, speaker and facilitator and has held workshops on security, visual thinking, design thinking and systems thinking in Europe, Canada, South America, West Africa and Asia. He has published extensively in the domains of physics and the social sciences. 

Dr Masys supports the University of Leicester (UK) as an associate tutor in their Distance MSc Program on Risk Crisis and Disaster Management.

Part I. Transformation in Policing: Technological Perspective

Introduction to Digital Policing

This chapter will provide an overview of Digital Policing with a main focus on the US and the UK police forces. As part of this overview, the chapter will explore how pervasive the use of technology in policing is and how day to day operations of police officers have changed compared to the past. As part of this study, the chapter aims to establish how often police follow patrols based on computer-forecast crime hot-spots, and what algorithmically based methods the police use when ranking people who are at risk of becoming victims or perpetrators of crime[1]^{, [2]}.

An Overview of AI, Big Data and Predictive Analytics in Digital Policing

This chapter will provide the readers with the necessary background knowledge in relation to what Artificial Intelligence, Big Data and Predictive Analytics are and how they are used within different sectors. The chapter will then proceed to discuss how these technologies are transforming traditional policing into modern, efficient policing.

A Study of Correlation between Big Data Policing and Reduction in Crime

There are currently few studies that have investigated the impact of Big Data Policing on the reductions in crime. Considering that these studies tend to be inconclusive¹ (Crime rates often relate to a number of factors such as economic and environmental forces that render it challenging to establish any underlying connection with a specific technology.), this chapter will aim to synthesise this research to determine to what extent BDP has facilitated reductions in crime.

Part II. The Promises

The Use of Big Data and Predictive Analytics in Modern Policing

This chapter will explore how Big Data and Predictive Analytics are transforming policing around the world. In particular, the chapter will focus on how the US' and the UK's police forces use these technologies to predict and identify individuals who might become perpetrators or victims of crime.

Application of Artificial Intelligence in Digital Policing

This chapter will explore how Big Data and Predictive Analytics are transforming policing around the world. In particular, the chapter will focus on how the US' and the UK's police forces use these technologies to predict and identify individuals who might become perpetrators or victims of crime.

Enterprise Geographic Information System and Digital Policing

This chapter will examine the ways in which Enterprise GIS supports policing operations. To this end, the chapter will explore how the implementation of an Enterprise GIS platform across a police services could facilitate data-driven decision making to address important questions such as where and when communities are most at risk, and how the police mitigate these risks[3].

Criminal Intelligence, Crime Pattern Analysis and Operational Policing

This chapter will investigate how intelligence analysis is used as a tool to understand crime and disorder and offer insight, clarity and context to decision makers. As part of this examination, a number of analytical techniques will be discussed including: regression and data mining techniques, GIS data mining, neural network, and support vector machine, etc. The chapter will discuss major theories of criminal behaviour such as routine activity theory, rational choice theory, and crime pattern theory.

Cell Site Analysis and ANPR Mapping

This chapter will discuss how law enforcement agencies deploy Cell Cire Analysis to determine the likely locations of a mobile phone using the detailed examination of historic call data records together with radio frequency network surveys. This discussion will also briefly draw upon the use Cell Site Analysis evidence by the criminal defence team as maps and schedules[4].

Part III. The Perils

The Dark Web and Digital Policing

This chapter will explore some of the most difficult challenges that the dark web and its marketplaces present to law enforcement agencies. Examples of these challenges will include those concerning digital forensic investigations of crimes, encryption and anonymity, etc.

Implications of Algorithm-Driven and Person-Based Predictive Policing

Person-based predictive policing involves the adoption of data to detect and investigate potential suspects or victims. This chapter will explore algorithm-driven policing and its associated threats to the security, privacy, and constitutional rights of citizens. Particularly, the chapter will focus on examining person-based policing systems and the targeting of individuals. The chapter will analyse elements such as racial bias, facial recognition, a lack of transparency, data error and the distortions of constitutional protections, all of which pose significant challenges to the design and implementation of workable person-based predictive strategies^{1, 2}.

Algorithmic Bias, Transparency and Data Error in Person-Based Predictive Policing

Person-based predictive policing involves the adoption of data to detect and investigate potential suspects or victims. This chapter will investigate person-based policing systems and the targeting of individuals. The chapter will analyse elements such as racial bias, facial recognition, a lack of transparency, data error and the distortions of constitutional protections, all of which pose significant challenges to the design and implementation of workable person-based predictive strategies^{1, 2}.

Policing and Probabilistic Predictions

Data can certainly enable police forces to make predictions which will assist them in expending their resources smarter. This chapter will argue that, however, a probabilistic prediction cannot be considered certainty. The chapter will go on to discuss ways through which police could harm innocent individuals when taking actions based on probabilities[5].

Surveillance Technologies, Human Rights and the Imbalance of Power

This chapter will argue that there has been an exponential growth in in web of police surveillance, thereby threatening freedoms, political expression, personal privacy and other human rights^{1, 2}.

Part IV. The Solutions

Balancing Crime Reduction with Civil Rights

This chapter will argue that although predictive policing could have significant impact on crime reduction, simultaneously, it threatens individual's civil liberties. The chapter observes that, as a result, care must be taken to ensure that predictive policing is deployed in a fair manner. To this end, the chapter will offer a number of practical recommendations with a view to balancing crime reduction based on predictive policing with civil rights⁵.

Tentative list of authors who might submit a chapter:

Prof. Iain Sutherland

Noroff University, Norway.

E: iain.sutherland@noroff.no

W: https://bit.ly/3qnOMH5

Professor. Mark Stamp

San Jose State University, USA.

E: mark.stamp@sjsu.edu

W: https://bit.ly/39BOPsG

Professor. Stuart Macdonald

Swansea University, UK.

E: s.macdonald@swansea.ac.uk

W: https://bit.ly/3mOWtUF

Dr. Kim-Kwang Raymond Choo

The University of Texas at San Antonio, USA.

E: raymond.Choo@utsa.edu

W: https://bit.ly/39F3qE2

Nick Furneaux

Director of CSITech Company

W: https://bit.ly/2VWm55X

Professor. Maura Conway

Dublin City University, Republic of Ireland.

E: maura.conway@dcu.ie

W: https://bit.ly/3qpcoLq

Dr. Phil Legg

University of West England, UK.

E: Phil.Legg@uwe.ac.uk

W: https://bit.ly/37GEV6s

Dr. Simon Parkinson

Huddersfield University, UK.

E: s.parkinson@hud.ac.uk

W: https://bit.ly/37LYFWH

Professor. Peter Sommer

Birmingham City University, UK.

E: peter.sommer@bcu.ac.uk

W: https://bit.ly/3qqCWvB

Andy Cuff

Computer Network Defence Ltd, USA and UK.

E: andy.cuff@cndltd.com

W: https://www.cndltd.com/

Dr. Z. Cliffe Schreuders

Leeds Beckett University, UK.

E: c.schreuders@leedsbeckett.ac.uk

W: https://bit.ly/39CVnHz

Professor. Hamid Jahankhani

Northumbria University, UK.

E: hamid.jahankhani@northumbria.ac.uk

W: https://bit.ly/3gvCE25

Jens Kirschner

Senior Computer Forensics Specialist at X-Ways Software Technology AG, Germany.

E: linkedin@jenskirschner.eu

W: https://bit.ly/33HoXYF

Lance Spitzner

Director, SANS Institute Founder, Honeynet Project, USA.

E: lance@spitzner.net

W: https://bit.ly/3onRxWO

Helen Olsen Bedford

Publisher, UKAuthority.com & UKA Live, UK.

E: helen@ukauthority.co.uk

W: https://www.ukauthority.com/

Responding to the Threats of Big Data and Predictive Analytics Policing

This chapter discusses a number of practical ways by which individual's human rights can be protected against threats of Big Data Policing.

Best Practices and Guidance for Police Use of Facial Recognition

This chapter will focus on ways that could be adopted to address ethical, privacy and legal challenges posed by the police use of overt surveillance camera systems integrating facial recognition technology. To this end, the chapter will recommend best practices and guidance that could be considered to address these challenges.