TY - CHAP
T1 - Exploring Applications and Implications of Big Data Predictive Analytics in Policing Cyberspace
AU - Pinney, Joel
AU - Bentotahewa, Vibhushinie
AU - Tomlinson, Matthew
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2024/11/27
Y1 - 2024/11/27
N2 - As the world continues to become a data-driven society, the applications of using data extends beyond traditional uses and introduces further avenues for considering how we protect users’ data. Specifically, the increasing reliance on big data analytics in law enforcement has raised questions regarding privacy, individual rights, and the potential for bias in decision-making. This chapter examines how predictive analytics tools are employed to identify cyber threats, predict criminal activities and behaviours, and enhance proactive policing measures. Furthermore, it delves into the ethical challenges associated with the collection and analysis of vast amounts of personal data, emphasising the importance of balancing security needs with privacy concerns. GDPR, as a prominent data protection framework, is scrutinised in the context of policing cyberspace, evaluating its effectiveness in safeguarding the public’s rights while permitting necessary data processing for law enforcement. Moreover, assessing its ability to balance the safeguarding of users’ privacy rights whilst continuing to proactively police. By shedding light on the ethical and legal dimensions, this book chapter contributes to a comprehensive understanding of the complex interplay between big data analytics, policing strategies, and the protection of individual rights in the digital age.
AB - As the world continues to become a data-driven society, the applications of using data extends beyond traditional uses and introduces further avenues for considering how we protect users’ data. Specifically, the increasing reliance on big data analytics in law enforcement has raised questions regarding privacy, individual rights, and the potential for bias in decision-making. This chapter examines how predictive analytics tools are employed to identify cyber threats, predict criminal activities and behaviours, and enhance proactive policing measures. Furthermore, it delves into the ethical challenges associated with the collection and analysis of vast amounts of personal data, emphasising the importance of balancing security needs with privacy concerns. GDPR, as a prominent data protection framework, is scrutinised in the context of policing cyberspace, evaluating its effectiveness in safeguarding the public’s rights while permitting necessary data processing for law enforcement. Moreover, assessing its ability to balance the safeguarding of users’ privacy rights whilst continuing to proactively police. By shedding light on the ethical and legal dimensions, this book chapter contributes to a comprehensive understanding of the complex interplay between big data analytics, policing strategies, and the protection of individual rights in the digital age.
KW - Big data
KW - Ethical
KW - Predictive analytics
KW - Predictive policing
KW - Privacy
UR - http://www.scopus.com/inward/record.url?scp=85210433966&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-72821-1_1
DO - 10.1007/978-3-031-72821-1_1
M3 - Chapter
AN - SCOPUS:85210433966
T3 - Advanced Sciences and Technologies for Security Applications
SP - 1
EP - 18
BT - Advanced Sciences and Technologies for Security Applications
PB - Springer
ER -