Mitigating Evasion Attacks in Fog Computing Resource Provisioning Through Proactive Hardening
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. ...
| Authors | Younes Salmi, Hanna Bogucka |
|---|---|
| Primary category | cs.CR |
| Published | 26 March 2026 |
| Last updated at source | 26 March 2026 |
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