Identifying Threats, Cybercrime and Digital Forensic Opportunities in Smart City Infrastructure via Threat Modeling

Autor: Tok, Yee Ching, Chattopadhyay, Sudipta
Rok vydání: 2022
Předmět:
Zdroj: Forensic Science International: Digital Investigation, Volume 45, 2023
Druh dokumentu: Working Paper
DOI: 10.1016/j.fsidi.2023.301540
Popis: Technological advances have enabled multiple countries to consider implementing Smart City Infrastructure to provide in-depth insights into different data points and enhance the lives of citizens. Unfortunately, these new technological implementations also entice adversaries and cybercriminals to execute cyber-attacks and commit criminal acts on these modern infrastructures. Given the borderless nature of cyber attacks, varying levels of understanding of smart city infrastructure and ongoing investigation workloads, law enforcement agencies and investigators would be hard-pressed to respond to these kinds of cybercrime. Without an investigative capability by investigators, these smart infrastructures could become new targets favored by cybercriminals. To address the challenges faced by investigators, we propose a common definition of smart city infrastructure. Based on the definition, we utilize the STRIDE threat modeling methodology and the Microsoft Threat Modeling Tool to identify threats present in the infrastructure and create a threat model which can be further customized or extended by interested parties. Next, we map offences, possible evidence sources and types of threats identified to help investigators understand what crimes could have been committed and what evidence would be required in their investigation work. Finally, noting that Smart City Infrastructure investigations would be a global multi-faceted challenge, we discuss technical and legal opportunities in digital forensics on Smart City Infrastructure.
Comment: Updated to include amendments from peer review process. Accepted in Forensic Science International: Digital Investigation
Databáze: arXiv