Adaptive Threat Attribution in Cross-Platform Environments: Developing a Framework for Fingerprinting APT Groups Across Cloud and On-Premise Infrastructure
Authors/Creators
- 1. Department of Electrical and Computer Engineering, Institution: Stevens Institute of Technology, Hoboken NJ.
- 2. Department of Library and Information Science, Kyungpook National University.
- 3. Department of Technology innovation management, Carleton university.
- 4. Department of Computer Science, University of Jos, Nigeria.
Description
The proliferation of hybrid cloud-on-premise infrastructures has fundamentally altered the threat landscape, creating new challenges for Advanced Persistent Threat (APT) attribution. This research presents a novel framework for adaptive threat attribution that leverages behavioral analytics, technical indicators, and environmental context to fingerprint APT groups across heterogeneous computing environments. Our methodology combines traditional Tactics, Techniques, and Procedures (TTPs) analysis with cloud-native threat indicators and infrastructure-agnostic behavioral patterns. Through analysis of 847 APT incidents across Fortune 500 enterprises from 2022-2024, we demonstrate that our framework achieves 87.3% accuracy in APT group attribution, representing a 23% improvement over existing methodologies. The framework addresses critical gaps in cross-platform threat intelligence by incorporating cloud service provider artifacts, containerized environment indicators, and hybrid infrastructure telemetry into attribution models.
Files
WJARR-2025-2349.pdf
Files
(535.2 kB)
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