QEMU-Based Fault Injection for a System-Level Analysis of Software Countermeasures Against Fault Attacks

Höller, Andrea; Krieg, Armin; Rauter, Tobias; Iber, Johannes; Kreiner, Christian

doi:10.1109/dsd.2015.79

Cited by 25 publications

(20 citation statements)

References 10 publications

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“…This identifies yet another challenge area for the software based approaches: the limitations of the tools used in their software process. For many software based approaches there are specific tools developed for them, that tend to lack breadth and maturity [15,27]. For others that employ tools (often from other domains), these tools tend to have limitations of their own such as being unable to handle everything required (e.g.…”

Section: Challengesmentioning

confidence: 99%

“…Another significant challenge for the software based approaches are in the accuracy and breadth of the tools they use. Various works have applied techniques that build upon exploiting tools to transform between languages or models [14,15] or that rely on tools for checking or verifying [27]. However, many of these tools have their own limitations.…”

Section: Introductionmentioning

confidence: 99%

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The State of Fault Injection Vulnerability Detection

Given-Wilson

Jafri

Legay

2018

Lecture Notes in Computer Science

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Fault injection is a well known method to test the robustness and security vulnerabilities of software. Fault injections can be explored by simulations (cheap, but not validated) and hardware experiments (true, but very expensive). Recent simulation works have started to apply formal methods to the detection, analysis, and prevention of fault injection attacks to address verifiability. However, these approaches are ad-hoc and extremely limited in architecture, fault model, and breadth of application. Further, there is very limited connection between simulation results and hardware experiments. Recent work has started to consider broad spectrum simulation approaches that can cover many fault models and relatively large programs. Similarly the connection between these broad spectrum simulations and hardware experiments is being validated to bridge the gap between the two approaches. This presentation highlights the latest developments in applying formal methods to fault injection vulnerability detection, and validating software and hardware results with one another.

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Section: Challengesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The State of Fault Injection Vulnerability Detection

Given-Wilson

Jafri

Legay

2018

Lecture Notes in Computer Science

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“…In Ref. [29] a tool that operates in QEMU (an open source machine emulator and virtualizer) is presented, injecting faults into the CPU registers, RAM data, storage system and networking I/O. In order to provide a larger scope of fault injection targets, Ref.…”

Section: Swifi In Operating Systemmentioning

confidence: 99%

“…In order to provide a larger scope of fault injection targets, Ref. [29] proposes to inject faults into the environment of a virtual machine; moreover, this method has a high complexity.…”

Section: Swifi In Operating Systemmentioning

confidence: 99%

KITO tool: A fault injection environment in Linux kernel data structures

Velasco

Montrucchio

Rebaudengo

2016

Microelectronics Reliability

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“…During the first design phases, they provide the ability to explore different architectures and ideas, allowing to collect data regarding functionality, performance, energy consumption, with reduced development cost and time compared to physical prototypes. This is true for functional and performance emulators [11], [12], energy consumption emulators [13], [14] and fault emulators [15], [16].…”

Section: Related Work and Contributionmentioning

confidence: 99%

AppropinQuo: A Platform Emulator for Exploring the Approximate Memory Design Space

Stazi

Mastrandrea

Olivieri

et al. 2018

2018 New Generation of CAS (NGCAS)

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In this work we present AppropinQuo, a flexible and configurable emulator for embedded platforms with approximate memory. The emulator includes models of the effects of approximate memory circuits and architectures, that depend on the internal structure and organization of the cells. The ability to emulate a complete platform, including CPU, peripherals and hardware-software interactions, is particularly important since it allows to execute the application as on the real board, reproducing the effects of errors on output. In fact, output quality is related not only to error rate but it also depends on the application, implementation and its data representation.AppropinQuo allows to run actual applications and operating system as on the physical platform, to analyze the behavior and to expose the effects of specific approximate memory circuits and architectures on output quality. By exploring the design space regarding approximate memories, a complete characterization of the application is possible, as a step toward the determination of the trade-off between saved energy and output quality (energyquality tradeoff).

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QEMU-Based Fault Injection for a System-Level Analysis of Software Countermeasures Against Fault Attacks

Cited by 25 publications

References 10 publications

The State of Fault Injection Vulnerability Detection

The State of Fault Injection Vulnerability Detection

KITO tool: A fault injection environment in Linux kernel data structures

AppropinQuo: A Platform Emulator for Exploring the Approximate Memory Design Space

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