Biblio

Filters: Author is Guo, Xiaolong  [Clear All Filters]
2021-11-08
Zhu, Huifeng, Guo, Xiaolong, Jin, Yier, Zhang, Xuan.  2020.  PowerScout: A Security-Oriented Power Delivery Network Modeling Framework for Cross-Domain Side-Channel Analysis. 2020 Asian Hardware Oriented Security and Trust Symposium (AsianHOST). :1–6.
The growing complexity of modern electronic systems often leads to the design of more sophisticated power delivery networks (PDNs). Similar to other system-level shared resources, the on-board PDN unintentionally introduces side channels across design layers and voltage domains, despite the fact that PDNs are not part of the functional design. Recent work have demonstrated that exploitation of the side channel can compromise the system security (i.e. information leakage and fault injection). In this work, we systematically investigate the PDN-based side channel as well as the countermeasures. To facilitate our goal, we develop PowerScout, a security-oriented PDN simulation framework that unifies the modeling of different PDN-based side-channel attacks. PowerScout performs fast nodal analysis of complex PDNs at the system level to quantitatively evaluate the severity of side-channel vulnerabilities. With the support of PowerScout, for the first time, we validate PDN side-channel attacks in literature through simulation results. Further, we are able to quantitatively measure the security impact of PDN parameters and configurations. For example, towards information leakage, removing near-chip capacitors can increase intra-chip information leakage by a maximum of 23.23dB at mid-frequency and inter-chip leakage by an average of 31.68dB at mid- and high-frequencies. Similarly, the optimal toggling frequency and duty cycle are derived to achieve fault injection attacks with higher success rate and more precise control.
2020-02-26
Guo, Xiaolong, Zhu, Huifeng, Jin, Yier, Zhang, Xuan.  2019.  When Capacitors Attack: Formal Method Driven Design and Detection of Charge-Domain Trojans. 2019 Design, Automation Test in Europe Conference Exhibition (DATE). :1727–1732.

The rapid growth and globalization of the integrated circuit (IC) industry put the threat of hardware Trojans (HTs) front and center among all security concerns in the IC supply chain. Current Trojan detection approaches always assume HTs are composed of digital circuits. However, recent demonstrations of analog attacks, such as A2 and Rowhammer, invalidate the digital assumption in previous HT detection or testing methods. At the system level, attackers can utilize the analog properties of the underlying circuits such as charge-sharing and capacitive coupling effects to create information leakage paths. These new capacitor-based vulnerabilities are rarely covered in digital testings. To address these stealthy yet harmful threats, we identify a large class of such capacitor-enabled attacks and define them as charge-domain Trojans. We are able to abstract the detailed charge-domain models for these Trojans and expose the circuit-level properties that critically contribute to their information leakage paths. Aided by the abstract models, an information flow tracking (IFT) based solution is developed to detect charge-domain leakage paths and then identify the charge-domain Trojans/vulnerabilities. Our proposed method is validated on an experimental RISC microcontroller design injected with different variants of charge-domain Trojans. We demonstrate that successful detection can be accomplished with an automatic tool which realizes the IFT-based solution.

2020-09-18
Guo, Xiaolong, Dutta, Raj Gautam, He, Jiaji, Tehranipoor, Mark M., Jin, Yier.  2019.  QIF-Verilog: Quantitative Information-Flow based Hardware Description Languages for Pre-Silicon Security Assessment. 2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST). :91—100.
Hardware vulnerabilities are often due to design mistakes because the designer does not sufficiently consider potential security vulnerabilities at the design stage. As a result, various security solutions have been developed to protect ICs, among which the language-based hardware security verification serves as a promising solution. The verification process will be performed while compiling the HDL of the design. However, similar to other formal verification methods, the language-based approach also suffers from scalability issue. Furthermore, existing solutions either lead to hardware overhead or are not designed for vulnerable or malicious logic detection. To alleviate these challenges, we propose a new language based framework, QIF-Verilog, to evaluate the trustworthiness of a hardware system at register transfer level (RTL). This framework introduces a quantified information flow (QIF) model and extends Verilog type systems to provide more expressiveness in presenting security rules; QIF is capable of checking the security rules given by the hardware designer. Secrets are labeled by the new type and then parsed to data flow, to which a QIF model will be applied. To demonstrate our approach, we design a compiler for QIF-Verilog and perform vulnerability analysis on benchmarks from Trust-Hub and OpenCore. We show that Trojans or design faults that leak information from circuit outputs can be detected automatically, and that our method evaluates the security of the design correctly.
2017-12-20
Dutta, R. G., Guo, Xiaolong, Zhang, Teng, Kwiat, K., Kamhoua, C., Njilla, L., Jin, Y..  2017.  Estimation of safe sensor measurements of autonomous system under attack. 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC). :1–6.
The introduction of automation in cyber-physical systems (CPS) has raised major safety and security concerns. One attack vector is the sensing unit whose measurements can be manipulated by an adversary through attacks such as denial of service and delay injection. To secure an autonomous CPS from such attacks, we use a challenge response authentication (CRA) technique for detection of attack in active sensors data and estimate safe measurements using the recursive least square algorithm. For demonstrating effectiveness of our proposed approach, a car-follower model is considered where the follower vehicle's radar sensor measurements are manipulated in an attempt to cause a collision.