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Bibliographic Details
Main Authors: Chenet, Cristiano Pegoraro, Zhang, Ziteng, Savino, Alessandro, Di Carlo, Stefano
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.10282
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author Chenet, Cristiano Pegoraro
Zhang, Ziteng
Savino, Alessandro
Di Carlo, Stefano
author_facet Chenet, Cristiano Pegoraro
Zhang, Ziteng
Savino, Alessandro
Di Carlo, Stefano
contents This work evaluates how well hardware-based approaches detect stack buffer overflow (SBO) attacks in RISC-V systems. We conducted simulations on the PULP platform and examined micro-architecture events using semi-supervised anomaly detection techniques. The findings showed the challenge of detection performance. Thus, a potential solution combines software and hardware-based detectors concurrently, with hardware as the primary defense. The hardware-based approaches present compelling benefits that could enhance RISC-V-based architectures.
format Preprint
id arxiv_https___arxiv_org_abs_2406_10282
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hardware-based stack buffer overflow attack detection on RISC-V architectures
Chenet, Cristiano Pegoraro
Zhang, Ziteng
Savino, Alessandro
Di Carlo, Stefano
Cryptography and Security
This work evaluates how well hardware-based approaches detect stack buffer overflow (SBO) attacks in RISC-V systems. We conducted simulations on the PULP platform and examined micro-architecture events using semi-supervised anomaly detection techniques. The findings showed the challenge of detection performance. Thus, a potential solution combines software and hardware-based detectors concurrently, with hardware as the primary defense. The hardware-based approaches present compelling benefits that could enhance RISC-V-based architectures.
title Hardware-based stack buffer overflow attack detection on RISC-V architectures
topic Cryptography and Security
url https://arxiv.org/abs/2406.10282