scholarly journals A multi-flow information flow tracking approach for proving quantitative hardware security properties

2021 ◽  
Vol 26 (1) ◽  
pp. 62-71
Author(s):  
Yu Tai ◽  
Wei Hu ◽  
Lu Zhang ◽  
Dejun Mu ◽  
Ryan Kastner
2021 ◽  
Vol 54 (4) ◽  
pp. 1-39
Author(s):  
Wei Hu ◽  
Armaiti Ardeshiricham ◽  
Ryan Kastner

Information flow tracking (IFT) is a fundamental computer security technique used to understand how information moves through a computing system. Hardware IFT techniques specifically target security vulnerabilities related to the design, verification, testing, manufacturing, and deployment of hardware circuits. Hardware IFT can detect unintentional design flaws, malicious circuit modifications, timing side channels, access control violations, and other insecure hardware behaviors. This article surveys the area of hardware IFT. We start with a discussion on the basics of IFT, whose foundations were introduced by Denning in the 1970s. Building upon this, we develop a taxonomy for hardware IFT. We use this to classify and differentiate hardware IFT tools and techniques. Finally, we discuss the challenges yet to be resolved. The survey shows that hardware IFT provides a powerful technique for identifying hardware security vulnerabilities, as well as verifying and enforcing hardware security properties.


Author(s):  
Laurent Georget ◽  
Mathieu Jaume ◽  
Guillaume Piolle ◽  
Frédéric Tronel ◽  
Valérie Viet Triem Tong

Author(s):  
Muhammad Abdul Wahab ◽  
Pascal Cotret ◽  
Mounir Nasr Allah ◽  
Guillaume Hiet ◽  
Vianney Lapotre ◽  
...  

Author(s):  
Anna Trikalinou ◽  
Nikolaos Bourbakis

Memory errors have long been a critical security issue primarily for C/C++ programming languages and are still considered one of the top three most dangerous software errors according to the MITRE ranking. In this paper the authors focus on their exploitation via control-flow hijacking and data-only attacks (stack, and partially heap (G. Novarck & E. Berger, 2010)) by proposing a synergistic security methodology, which can accurately detect and thwart them. Their methodology is based on the Dynamic Information Flow Tracking (DIFT) technique and improves its data-only attack detection by utilizing features from the Reverse Stack Execution (RSE) security technique. Thus, the authors can significantly lower the resource consumption of the latter methodology, while increasing the former's accuracy. Their proof-of-concept compiler implementation verifies their assumptions and is able to protect vulnerable C programs against various real-world attack scenarios.


2017 ◽  
Vol 52 (4) ◽  
pp. 555-568
Author(s):  
Andrew Ferraiuolo ◽  
Rui Xu ◽  
Danfeng Zhang ◽  
Andrew C. Myers ◽  
G. Edward Suh

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