Towards Robust Real-Time Hardware-based Mobile Malware Detection using Multiple Instance Learning Formulation

arXiv:2404.13125v1 Announce Type: cross
Abstract: This study introduces RT-HMD, a Hardware-based Malware Detector (HMD) for mobile devices, that refines malware representation in segmented time-series through a Multiple Instance Learning (MIL) approach. We address the mislabeling issue in real-time HMDs, where benign segments in malware time-series incorrectly inherit malware labels, leading to increased false positives. Utilizing the proposed Malicious Discriminative Score within the MIL framework, RT-HMD effectively identifies localized malware behaviors, thereby improving the predictive accuracy. Empirical analysis, using a hardware …

abstract arxiv cs.cr cs.lg detection devices hardware instance issue malware malware detection mil mobile mobile devices multiple real-time representation robust series study through type