CyberIntel ⬡ News
★ Saved ◆ Cyber Reads
← Back ◬ AI & Machine Learning May 19, 2026

STRIKE: A Structured Taxonomy of Cybercrime for Risk, Impact, Knowledge, and Evolution

arXiv Security Archived May 19, 2026 ✓ Full text saved

arXiv:2605.16589v1 Announce Type: new Abstract: Cybercrime has grown exponentially in both scale and sophistication, posing significant threats. As attack methods evolve rapidly, traditional classification schemes often fail to capture the complexity and diversity of modern threats. To address this gap, we introduce STRIKE,a Structured Taxonomy for Risk, Impact, Knowledge, and Emerging Threats, which provides a unified, multi-dimensional framework for categorizing cybercrimes. STRIKE spans both

Full text archived locally
✦ AI Summary · Claude Sonnet


    Computer Science > Cryptography and Security [Submitted on 15 May 2026] STRIKE: A Structured Taxonomy of Cybercrime for Risk, Impact, Knowledge, and Evolution Melissa Pappy, Linh Nguyen, Suman Kumar, Byungkwan Jung, Bernard Chen Cybercrime has grown exponentially in both scale and sophistication, posing significant threats. As attack methods evolve rapidly, traditional classification schemes often fail to capture the complexity and diversity of modern threats. To address this gap, we introduce STRIKE,a Structured Taxonomy for Risk, Impact, Knowledge, and Emerging Threats, which provides a unified, multi-dimensional framework for categorizing cybercrimes. STRIKE spans both conventional and emerging domains, including ransomware, phishing, network intrusion, child sexual abuse material (CSAM), cryptojacking, deepfakes, and supply chain attacks. It organizes threats using criteria such as attack vectors, adversarial tactics, societal impact, detection techniques, and mitigation strategies. Alongside the taxonomy, we review recent advances in detection methodologies and present a response workflow to assist practitioners under active threat conditions. This work offers researchers, security professionals, and policymakers a practical foundation for threat analysis, comparative evaluation, and adaptive cyber defense. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.16589 [cs.CR]   (or arXiv:2605.16589v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.16589 Focus to learn more Journal reference: In Communications in Computer and Information Science, vol 2740. Springer (2026) Related DOI: https://doi.org/10.1007/978-3-032-14893-3_14 Focus to learn more Submission history From: Suman Kumar [view email] [v1] Fri, 15 May 2026 19:48:16 UTC (1,819 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
    💬 Team Notes
    Article Info
    Source
    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    May 19, 2026
    Archived
    May 19, 2026
    Full Text
    ✓ Saved locally
    Open Original ↗