AutoCC: Automatic Discovery of Covert Channels in Time-Shared Hardware


연구 분야: Verification



학회: MICRO '23: Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture


초록

Covert channels enable information leakage between security domains that should be isolated by observing execution differences in shared hardware. These channels can appear in any stateful shared resource, including caches, predictors, and accelerators. Previous works have identified many vulnerable components, demonstrating and defending against attacks via reverse engineering. However, this approach requires much human effort and reasoning. With the Cambrian explosion of specialized hardware, it is becoming increasingly difficult to identify all vulnerabilities manually. To tackle this challenge, we propose AutoCC, a methodology that leverages formal property verification (FPV) to automatically discover covert channels in hardware that is shared between processes. AutoCC operates at the register-transfer level (RTL) to exhaustively examine any machine state left by a process after a context switch that creates an execution difference. Upon finding such a difference, AutoCC provides a precise execution trace showing how the information was encoded into the machine state and recovered. Leveraging AutoCC’s flow to generate FPV testbenches that apply our methodology, we evaluated it on four open-source hardware projects, including two RISC-V cores and two accelerators. Without hand-written code or directed tests, AutoCC uncovered known covert channels (within minutes instead of many hours of test-driven emulations) and unknown ones. Although AutoCC is primarily intended to find covert channels, our evaluation has also found RTL bugs, demonstrating that AutoCC is an effective tool to test both the security and reliability of hardware designs.


Author Profile
Marcelo Orenes-Vera

Princeton University United States of America

United States
Author Profile
Hyunsung Yun

Princeton University USA

United States
Author Profile
Nils Wistoff

ETH Zürich Switzerland

Ethiopia

📄 논문 정보

발행 연도 2023년
인용수 5
출판 국가 Ethiopia, Australia, United States
사이트 ACM
좋아요 수 0

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