Zero-Day Hardware-Supported Malware Detection of Stack Buffer Overflow Attacks: An Application Exploiting the CV32e40p RISC-V Core

The RISC-V architecture has become increasingly popular due to its open-source nature and flexibility, making it susceptible to various security attacks, such as Stack Buffer Overflow (SBO) attacks. It is crucial to effectively detect these attacks to ensure the security of RISC-V systems. This study explores Hardware-Supported Malware Detection (HMD) techniques for identifying these security threats. Using the CV32e40p RISC-V platform, we conducted simulations to assess the effectiveness of anomaly-based HMD methods in detecting SBO attacks by analyzing hardware microarchitectural events. The findings demonstrate the potential of these approaches but also reveal significant challenges in detection performance. These elements are essential for advancing the security capabilities of HMD systems in RISC-V environments.

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Publication Details

Published
2025-03-11
DOI
https://doi.org/10.1109/lats65346.2025.10963939
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.49

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article

Zero-Day Hardware-Supported Malware Detection of Stack Buffer Overflow Attacks: An Application Exploiting the CV32e40p RISC-V Core

Cristiano Pegoraro Chenet, Stefano Di Carlo, Alessandro Savino
1 citations
Advanced Malware Detection Techniques
1.49
article

Zero-Day Hardware-Supported Malware Detection of Stack Buffer Overflow Attacks: An Application Exploiting the CV32e40p RISC-V Core

Cristiano Pegoraro Chenet, Stefano Di Carlo, Alessandro Savino
article en
1 citations

Abstract

The RISC-V architecture has become increasingly popular due to its open-source nature and flexibility, making it susceptible to various security attacks, such as Stack Buffer Overflow (SBO) attacks. It is crucial to effectively detect these attacks to ensure the security of RISC-V systems. This study explores Hardware-Supported Malware Detection (HMD) techniques for identifying these security threats. Using the CV32e40p RISC-V platform, we conducted simulations to assess the effectiveness of anomaly-based HMD methods in detecting SBO attacks by analyzing hardware microarchitectural events. The findings demonstrate the potential of these approaches but also reveal significant challenges in detection performance. These elements are essential for advancing the security capabilities of HMD systems in RISC-V environments.

Politecnico di Torino (IT)
European Commission
Openalex Percentile: Top 20%
Advanced Malware Detection Techniques
1.49
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