An ASCON AOP-SystemC Environment for Security Fault Analysis Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.3390/sym16030348
Cryptographic devices’ complexity necessitates fast security simulation environments against fault attacks. SystemC, a promising candidate in Electronic System Levels (ESLs), can achieve higher simulation speeds while maintaining accuracy and reliability, and its modular and hierarchical design allows for efficient modeling of complex cryptographic algorithms and protocols. However, code modification is required for fault injection and detection. Aspect-Oriented Programming (AOP) can test cryptographic models’ robustness without modifications, potentially replacing real cryptanalysis schemes and reducing the time and effort required for fault injection and detection. Through the utilization of a fault injection/detection environment, this paper presents a novel approach to simulating the security fault attacks of ASCON cryptographic systems at the ESL. The purpose of this methodology is to evaluate the resistance of ASCON SystemC models against fault attacks. The proposed methodology leverages the advantages of AOP to enhance the fault injection and detection process. By applying AOP techniques, we inject faults into the SystemC models without making any changes to the main codebase. This approach not only improves the efficiency of testing cryptographic systems but also ensures that the main functionality remains intact during the fault injection process. The methodology was validated using three scenarios and SystemC ASCON as a case study. The first simulation involved evaluating fault detection capabilities, the second focused on the impact of AOP on executable file size and simulation time, and the third focused on the ESL impact on the ASCON design process. Simulation results show that this methodology can perfectly evaluate the robustness of the ASCON design against fault injection attacks with no significant impact on simulation time and file executable size. Additionally, the simulation results prove that the ASCON development life cycle at the ESL reduces the amount of time devoted to the design procedure by 83.34%, and the ASCON security attack simulations at the ESL decrease the simulation time by 40% compared to the register transfer level (RTL).
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/sym16030348
- https://www.mdpi.com/2073-8994/16/3/348/pdf?version=1710405288
- OA Status
- gold
- Cited By
- 2
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392817291
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392817291Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/sym16030348Digital Object Identifier
- Title
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An ASCON AOP-SystemC Environment for Security Fault AnalysisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-03-14Full publication date if available
- Authors
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Hassen Mestiri, Imen Barraj, Mouna Bedoui, Mohsen MachhoutList of authors in order
- Landing page
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https://doi.org/10.3390/sym16030348Publisher landing page
- PDF URL
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https://www.mdpi.com/2073-8994/16/3/348/pdf?version=1710405288Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2073-8994/16/3/348/pdf?version=1710405288Direct OA link when available
- Concepts
-
SystemC, Computer science, Fault injection, Embedded system, Executable, Robustness (evolution), Fault detection and isolation, Cryptography, Robustness testing, Distributed computing, Reliability engineering, Software, Algorithm, Operating system, Artificial intelligence, Actuator, Chemistry, Gene, Biochemistry, EngineeringTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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