Index Randomization with Dual SRAM-PUF for Spectre Mitigation in RISC-V Branch Predictors

Spectre attacks utilize branch prediction vulnerabilities to threaten processor security. In this paper, we propose a dual SRAM-PUF branch prediction index enhancement mechanism for BOOM processors in the RISC-V ecosystem. The index generation algorithm is reconfigured to prevent the targeted manipulation of the prediction table entries by incorporating the stochastic property of physical unclonable functions. Specifically, we adopt dual SRAM-PUF arrays to realize entropy-enhanced mapping of PC values, combine position swap and XOR obfuscation to generate index sequences resistant to speculative attacks, and optimize the index allocation strategy of prediction units. Chipyard experimental validation shows that the scheme can effectively mitigate Spectre V1/V2 variant attacks, with an average reduction of branch misprediction rate of about 1.5%, and a performance loss of less than 5% in the SPEC CPU2006 benchmark test. This research provides a hardware protection scheme for RISC-V processors that balances security and performance, which has practical significance for IoT and edge computing security architectures.

Authors

Institutions

Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/isaeece66033.2025.11160208
Primary Topic
Machine Learning and ELM
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Index Randomization with Dual SRAM-PUF for Spectre Mitigation in RISC-V Branch Predictors

Kai Nie, Mengyu Zhang, Xiao Zhang
Machine Learning and ELM
article

Index Randomization with Dual SRAM-PUF for Spectre Mitigation in RISC-V Branch Predictors

Kai Nie, Mengyu Zhang, Xiao Zhang
article en

Abstract

Spectre attacks utilize branch prediction vulnerabilities to threaten processor security. In this paper, we propose a dual SRAM-PUF branch prediction index enhancement mechanism for BOOM processors in the RISC-V ecosystem. The index generation algorithm is reconfigured to prevent the targeted manipulation of the prediction table entries by incorporating the stochastic property of physical unclonable functions. Specifically, we adopt dual SRAM-PUF arrays to realize entropy-enhanced mapping of PC values, combine position swap and XOR obfuscation to generate index sequences resistant to speculative attacks, and optimize the index allocation strategy of prediction units. Chipyard experimental validation shows that the scheme can effectively mitigate Spectre V1/V2 variant attacks, with an average reduction of branch misprediction rate of about 1.5%, and a performance loss of less than 5% in the SPEC CPU2006 benchmark test. This research provides a hardware protection scheme for RISC-V processors that balances security and performance, which has practical significance for IoT and edge computing security architectures.

PLA Information Engineering University (CN), Henan University of Technology (CN), Zhengzhou University (CN), Henan University of Engineering (CN)
Openalex Percentile: Top 87%
Machine Learning and ELM
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Index Randomization with Dual SRAM-PUF for Spectre Mitigation in RISC-V Branch Predictors — Kai Nie, Mengyu Zhang, et al. · (2025) | TGRS Research Map | TGRS