Emerging Cyber Threats and Modern Defense Strategies: A Systematic Analysis of Attack Taxonomies, Adversarial Trends, and Adaptive Security Frameworks

Authors

  • Omorinsola Oluwasegun Goriola

    British Computer Society. Newbridge Square, Swindon, United Kingdom
    Author
  • Azeez Rabiu

    Department of Computer Science, University of Ibadan, Nigeria.
    Author

DOI:

https://doi.org/10.4314/

Keywords:

cyber threat, security framework, ransomware-as-a-service, AI-augmented attacks, extended detection and response, supply chain security, IoT.

Abstract

The cybersecurity industry has seen a fundamental and, in many respects, irreversible shift in the last ten years, as the internet has become all-pervasive, AI has become a weapon, and attack surfaces have grown at an unprecedented rate, fueled by cloud adoption and the increasing number of Internet of Things (IoT) devices. This paper conducts a systematic, multi-method analysis of current cyber threat taxonomies and assesses the effectiveness of modern cyber-defensive architectures using a set of documented incidents from 2018 to 2024. We gathered and cross-checked data from three main sources: a longitudinal analysis of 1,247 publicly reported breaches from the Privacy Rights Clearinghouse and the Identity Theft Resource Center, structured interviews with 63 certified cybersecurity experts from eight nations in sub-Saharan Africa, and a controlled experimental testing of five potential defensive frameworks (Zero Trust Architecture (ZTA), AI-driven Security Operations Centers (AI-SOC), Extended Detection and Response (XDR), Deception Technology, and Quantum-Resistant Cryptography) of simulated adversarial campaigns based on the MITRE ATT&CK Enterprise Matrix. Our findings indicate that attacks enhanced by AI have risen by ~340% since 2020, with supply-chain intrusions and ransomware-as-a-service (RaaS) ecosystems representing the greatest proportion of financial damages. When defenders are deployed in a ZTA environment, the mean breach-detection latency is 67% less than when operating with traditional perimeter-based controls, and AI-SOC deployments achieved a 49% to 31% drop in false-positive alert rates. The point is, none of the plans was effective in all contexts, and combinations of various plans appear to be most effective. The research also points to a consistent readiness gap in developing-economy settings, where resources are limited, and the skills needed for advanced defences are lacking. We provide a three-layered, risk-proportionate defence model known as the Adaptive Cyber Resilience Framework (ACRF) and propose implementation pathways for it. The results of this research have important policy, procurement, and workforce development implications for both national cybersecurity policies and enterprise risk management policies.

 

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Published

2025-12-13

How to Cite

Emerging Cyber Threats and Modern Defense Strategies: A Systematic Analysis of Attack Taxonomies, Adversarial Trends, and Adaptive Security Frameworks. (2025). Communication In Physical Sciences, 12(8), 2509-2527. https://doi.org/10.4314/

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