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.

Zero-Day Hardware-Supported Malware Detection of Stack Buffer Overflow Attacks: An Application Exploiting the CV32e40p RISC-V Core / Chenet, Cristiano Pegoraro; Savino, Alessandro; Di Carlo, Stefano. - ELETTRONICO. - (2025), pp. 1-6. ( 26th IEEE Latin American Test Symposium, LATS 2025 San Andres Islas, Colombia 11-14 March 2025) [10.1109/lats65346.2025.10963939].

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

Chenet, Cristiano Pegoraro;Savino, Alessandro;Di Carlo, Stefano
2025

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.
2025
978-1-6654-7763-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3006133