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Windows Malware Detector as a Compound AI System: Trade-Offs in Accuracy, Efficiency, and Adversarial Robustness
Andrea Ponte, Luca Demetrio, Luca Oneto +2
Industrial Windows malware detectors are commonly described as Compound AI Systems composed of multiple heterogeneous components, including rule-based mechanisms as well as machine…
Architectural Backdoors in Vision-Language Model Supply Chains via Representation Steering
Maria Rosaria Briglia, Igor Maljkovic, Antonio Emanuele Cinà +3
Vision--Language Models (VLMs) are increasingly deployed through a model supply chain in which pretrained checkpoints, architecture definitions, text encoders, and exported computa…
Demystifying the Role of Rule-based Detection in AI Systems for Windows Malware Detection
Andrea Ponte, Luca Demetrio, Luca Oneto +3
Malware detection increasingly relies on AI systems that integrate signature-based detection with machine learning. However, these components are typically developed and combined i…
Empirical Quantification of Spurious Correlations in Malware Detection
Bianca Perasso, Ludovico Lozza, Andrea Ponte +3
End-to-end deep learning exhibits unmatched performance for detecting malware, but such an achievement is reached by exploiting spurious correlations -- features with high relevanc…