Analyzing Emerging Cybercrime Patterns and Enhancing Digital- ...
Abstract
Cybercrime in the Middle East and North Africa (MENA) is escalating faster than global averages, yet an evidence-based picture of how attack patterns interact with emerging counter-measures has been missing. This study bridges that gap through a mixed-methods approach combining longitudinal incident data (ransomware disclosures, Distributed Denial of Service [DDoS] volumes, breach-cost benchmarks from 2018 to 2025) with a regional survey of fifty-three digital-forensics professionals. Findings reveal that median breach losses rose to USD8.75 million in 2024 (79% above the world mean), confirmed ransomware victims multiplied nearly six-fold since 2018, and politically motivated DDoS traffic jumped 183% year-on-year—highlighting cyber spill-overs from regional tensions. Organizations that embedded explainable, artificial intelligence (AI)-enabled forensic workflows reported a one-third reduction in breach costs, compressed evidence-review cycles from weeks to days, and higher attribution accuracy in cases involving deepfakes or large botnets. Nevertheless, 78% of practitioners still struggle with data volumes, 72% with encryption barriers, and 55% with unclear evidentiary standards—underscoring that technology alone is insufficient. By consolidating economic benchmarks of MENA cybercrime and demonstrating—with field evidence—the conditional value of AI in digital forensics, the article contributes a novel regional baseline and offers a capability roadmap that prioritizes specialized training, cross-border threat-intelligence sharing, and harmonized legal frameworks as prerequisites for turning AI from a tactical upgrade into a strategic pillar of cyber-resilience.