Details
Originalsprache | Englisch |
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Titel des Sammelwerks | Computer Safety, Reliability, and Security - 41st International Conference, SAFECOMP 2022, Proceedings |
Untertitel | Computer Safety, Reliability, and Security |
Herausgeber/-innen | Mario Trapp, Francesca Saglietti, Marc Spisländer, Friedemann Bitsch |
Seiten | 207-221 |
Seitenumfang | 15 |
ISBN (elektronisch) | 978-3-031-14835-4 |
Publikationsstatus | Veröffentlicht - 2022 |
Publikationsreihe
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Band | 13414 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (elektronisch) | 1611-3349 |
Abstract
For systematic fault injection (FI), we deterministically re-execute a program, introduce faults, and observe the program outcome to assess its resilience in the presence of transient hardware faults. For this, simulation-assisted ISA-level FI provides a good trade-off between result quality and the required time to execute the FI campaign. However, for each architecture, this requires a specialized ISA simulator with tracing, injection, and error observation capabilities; a dependency that not only increases the bar for the exploration of ISA-level hardening mechanisms, but which can also deviate from the behavior of the actual hardware, especially when an error propagates through the system and triggers semantic edge cases. With SailFAIL, we propose a model-driven approach to derive FI platforms from Sail models, which formally describe the ISA semantics. Based on two existing (RISC-V, CHERI RISC-V) and one newly introduced (AVR) Sail models, we use the Sail toolchain to derive emulators that we combine with the FAIL* framework into multiple new FI platforms. Furthermore, we extend Sail to automatically introduce bit-wise dynamic register tracing into the emulator, which enables us to harvest bit-wise access information that we use to improve the well-known def-use pruning technique. Thereby, we further reduce the number of necessary injections by up to 19%.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Computer Safety, Reliability, and Security - 41st International Conference, SAFECOMP 2022, Proceedings: Computer Safety, Reliability, and Security. Hrsg. / Mario Trapp; Francesca Saglietti; Marc Spisländer; Friedemann Bitsch. 2022. S. 207-221 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13414 LNCS).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - SailFAIL
T2 - Model-Derived Simulation-Assisted ISA-Level Fault-Injection Platforms.
AU - Dietrich, Christian
AU - Bargholz, Malte
AU - Loeck, Yannick
AU - Budoj, Marcel
AU - Nedaskowskij, Luca
AU - Lohmann, Daniel
PY - 2022
Y1 - 2022
N2 - For systematic fault injection (FI), we deterministically re-execute a program, introduce faults, and observe the program outcome to assess its resilience in the presence of transient hardware faults. For this, simulation-assisted ISA-level FI provides a good trade-off between result quality and the required time to execute the FI campaign. However, for each architecture, this requires a specialized ISA simulator with tracing, injection, and error observation capabilities; a dependency that not only increases the bar for the exploration of ISA-level hardening mechanisms, but which can also deviate from the behavior of the actual hardware, especially when an error propagates through the system and triggers semantic edge cases. With SailFAIL, we propose a model-driven approach to derive FI platforms from Sail models, which formally describe the ISA semantics. Based on two existing (RISC-V, CHERI RISC-V) and one newly introduced (AVR) Sail models, we use the Sail toolchain to derive emulators that we combine with the FAIL* framework into multiple new FI platforms. Furthermore, we extend Sail to automatically introduce bit-wise dynamic register tracing into the emulator, which enables us to harvest bit-wise access information that we use to improve the well-known def-use pruning technique. Thereby, we further reduce the number of necessary injections by up to 19%.
AB - For systematic fault injection (FI), we deterministically re-execute a program, introduce faults, and observe the program outcome to assess its resilience in the presence of transient hardware faults. For this, simulation-assisted ISA-level FI provides a good trade-off between result quality and the required time to execute the FI campaign. However, for each architecture, this requires a specialized ISA simulator with tracing, injection, and error observation capabilities; a dependency that not only increases the bar for the exploration of ISA-level hardening mechanisms, but which can also deviate from the behavior of the actual hardware, especially when an error propagates through the system and triggers semantic edge cases. With SailFAIL, we propose a model-driven approach to derive FI platforms from Sail models, which formally describe the ISA semantics. Based on two existing (RISC-V, CHERI RISC-V) and one newly introduced (AVR) Sail models, we use the Sail toolchain to derive emulators that we combine with the FAIL* framework into multiple new FI platforms. Furthermore, we extend Sail to automatically introduce bit-wise dynamic register tracing into the emulator, which enables us to harvest bit-wise access information that we use to improve the well-known def-use pruning technique. Thereby, we further reduce the number of necessary injections by up to 19%.
KW - ISA-level fault injection
KW - Simulation-assisted fault injection
KW - Transient hardware faults
UR - http://www.scopus.com/inward/record.url?scp=85137992380&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-14835-4_14
DO - 10.1007/978-3-031-14835-4_14
M3 - Conference contribution
SN - 978-3-031-14834-7
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 207
EP - 221
BT - Computer Safety, Reliability, and Security - 41st International Conference, SAFECOMP 2022, Proceedings
A2 - Trapp, Mario
A2 - Saglietti, Francesca
A2 - Spisländer, Marc
A2 - Bitsch, Friedemann
ER -