Mitigating Evasion Attacks in Fog Computing Resource Provisioning Through Proactive Hardening

Computer Science > Cryptography and Security [Submitted on 26 Mar 2026] Mitigating Evasion Attacks in Fog Computing Resource Provisioning Through Proactive Hardening Younes Salmi, Hanna Bogucka This paper investigates the susceptibility to model integrity attacks that overload virtual machines assigned by the k-means algorithm used for resource provisioning in fog networks. The considered k-means algorithm runs two phases iteratively: offline clustering to form clusters of requested workload and online classification of new incoming requests into offline-created clusters. First, we consider an evasion attack against the classifier in the online phase. A threat actor launches an exploratory attack using query-based reverse engineering to discover the Machine Learning (ML) model (the clustering scheme). Then, a passive causative (evasion) attack is triggered in the offline phase. To defend the model, we suggest a proactive method using adversarial training to introduce attack robustness into the classifier. Our results show that our mitigation technique effectively maintains the stability of the resource provisioning system against attacks. Subjects: Cryptography and Security (cs.CR); Machine Learning (cs.LG) Cite as: arXiv:2603.25257 [cs.CR]   (or arXiv:2603.25257v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2603.25257 Focus to learn more Related DOI: https://doi.org/10.1109/EuCNC/6GSummit63408.2025.11036732 Focus to learn more Submission history From: Hanna Bogucka [view email] [v1] Thu, 26 Mar 2026 10:00:39 UTC (839 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.LG 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?)