Abstract

Social media has evolved into a critical channel for communication, expression, and public influence, but it has also become a prevalent avenue for cybercrime, particularly in digitally advanced nations such as the United Arab Emirates (UAE). The rising complexity of online offences, coupled with anonymisation tools and cross-border digital behaviour, has made the attribution of social-media-based cyber incidents increasingly challenging for law enforcement. In this context, artificial intelligence (AI) offers the potential to strengthen digital investigations by providing intelligent, scalable, and evidence-driven attribution capabilities. This research develops an AI-assisted Internet Protocol (IP) attribution framework tailored specifically for UAE law enforcement needs. The study addresses a significant gap in existing global models, which often overlook the UAE’s legal, cultural, linguistic, and infrastructural considerations. A fully synthetic dataset was generated for this research to ensure zero privacy or compliance risk. Machine learning techniques and forensic analytics were examined to determine their effectiveness in analysing behavioural patterns, device indicators, and network signals associated with suspicious online activity. The study further proposes a UAE-aligned system blueprint, designed to support digital evidence strengthening, enhance attribution confidence, and enable responsible operational use by cyber investigation units. The findings demonstrate that AI can meaningfully contribute to proactive cybercrime detection, attribution, and forensic intelligence when paired with regulatory alignment and contextual system design. Beyond technical validation, the thesis provides a strategic roadmap for integrating AI-based IP attribution into existing UAE law enforcement workflows, outlining adoption phases, governance requirements, and policy considerations. The research offers a foundational, ethical, and implementation-ready framework that can be extended through future real-world data collaboration and system-level deployment. Keywords: Social media cybercrime, Artificial Intelligence, IP attribution, Digital forensics, UAElawenforcement, Cybersecurity, Forensic analytics

Publication Date

12-2025

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Sanjay Modak

Advisor/Committee Member

Ioannis Karamitsos

Campus

RIT Dubai

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