XMD: An Expansive Hardware-telemetry based Mobile Malware Detector to enhance Endpoint Detection
Harshit Kumar, Biswadeep Chakraborty, Sudarshan Sharma, Saibal, Mukhopadhyay

TL;DR
XMD is a novel hardware-telemetry based mobile malware detector that leverages extensive subsystems telemetry to significantly outperform existing CPU core-focused detectors in accuracy and false positive rate.
Contribution
The paper introduces XMD, a hardware-telemetry based malware detector that utilizes expanded telemetry channels from multiple SoC subsystems, improving detection performance over existing HPC-based methods.
Findings
XMD improves detection accuracy by 32.91% over HPC-based detectors.
XMD achieves 86.54% detection rate with 2.9% false positives.
XMD outperforms signature-based Anti-Virus solutions on malware detection.
Abstract
Hardware-based Malware Detectors (HMDs) have shown promise in detecting malicious workloads. However, the current HMDs focus solely on the CPU core of a System-on-Chip (SoC) and, therefore, do not exploit the full potential of the hardware telemetry. In this paper, we propose XMD, an HMD that uses an expansive set of telemetry channels extracted from the different subsystems of SoC. XMD exploits the thread-level profiling power of the CPU-core telemetry, and the global profiling power of non-core telemetry channels, to achieve significantly better detection performance than currently used Hardware Performance Counter (HPC) based detectors. We leverage the concept of manifold hypothesis to analytically prove that adding non-core telemetry channels improves the separability of the benign and malware classes, resulting in performance gains. We train and evaluate XMD using hardware…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Network Security and Intrusion Detection · Anomaly Detection Techniques and Applications
