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.
World Journal of Advanced Research and Reviews, 2025, 27(02), 768-782
Article DOI: 10.30574/wjarr.2025.27.2.2912
Received on 04July 2025; revised on 09August; accepted on 12August 2025
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.
APT Attribution; Threat Intelligence; Cloud Security; Hybrid Infrastructure; Behavioral Analytics
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Nicholas Tetteh Ofoe, Aluko Ademola Mayokun, Anthony Edohen and Michael Okpotu Onoja. Adaptive Threat Attribution in Cross-Platform Environments: Developing a Framework for Fingerprinting APT Groups Across Cloud and On-Premise Infrastructure. World Journal of Advanced Research and Reviews, 2025, 27(02), 768-782. Article DOI: https://doi.org/10.30574/wjarr.2025.27.2.2912.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0