Realizing a security aware triple modular redundancy scheme for robust integrated circuits

Gunti, Nagendra Babu; Khatri, Aman; Lingasubramanian, Karthikeyan

doi:10.1109/vlsi-soc.2014.7004183

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…The use of TMR to thwart HT insertion has been proposed in [10], [4], [5] by N. Gunti et al In such a TMR based method, an HT has to be introduced in at least two copies in order not to be blocked by the majority voter. Authors claim that such duplication of a potential HT makes it relatively big, therefore also relatively easy to detect through side-channel based techniques.…”

Section: B Ht Prevention Methods Based On Redundancymentioning

confidence: 99%

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Using Approximate Circuits Against Hardware Trojans

et al. 2023

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Hardware Trojans (HTs) are malicious alterations in Integrated Circuits (ICs) that pose an important threat to safety-critical systems. Many techniques based on logic testing or side-channel analysis have been proposed in the literature aiming at detecting such malicious modifications in fabricated ICs. The detection of HTs is becoming more challenging with the shrinking of the technology and the impact of process variations. Therefore there is a need to neutralize the effect of HTs when the typical detection mechanism fails. In this work, we propose to tackle the effect of HTs by leveraging fault-tolerant techniques like Triple Modular Redundancy (TMR). More specifically, we propose to use an approximate TMR in order to neutralize the effects of HTs while saving area and increasing the complexity of inserting HTs. The efficiency of the proposed approach has been evaluated by using the ISCAS'85 benchmarks and stealthy ad-hoc HTs.

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Section: B Ht Prevention Methods Based On Redundancymentioning

confidence: 99%

“…As in other similar works that use TMR as neutralization method [10], [4], [5], we have selected the ISCAS'85 benchmarks as target circuits [12]. We have selected two circuits -c499 and c7552 -based on their different sizes and functionalities, to carry out a thoroughly study about the proposed approach.…”

Section: A Methodologymentioning

confidence: 99%

Using Approximate Circuits Against Hardware Trojans

et al. 2023

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“…In the past decade, there are many hardware Trojan detection works, including the side-channel analysis based detection approaches [5]- [9] and logic testing approaches [10], [11]. Some design-for-security approaches are also proposed to facilitate hardware Trojan detection or prevent hardware Trojan insertion, e.g., built-in self-authentication technique to prevent inserting hardware Trojans [12], redundancy-based protection approach based on Trojan tolerance that modifies the application mapping process to provide high-level of protection against Trojans in FPGA [13], the approach promoting smart employment of circuit redundancy to counter Trojans in 3PIP cores [14], and the approach using a selective Triple Modular Redundancy (TMR) scheme to mask the effect of Trojans along with transient errors [15]. Most of them require golden chips or golden models for reference.…”

Section: Introductionmentioning

confidence: 99%

“…for j = 1 to R do 15: initialize the disagreement measure matrix DIS l×(R−l) and average disagreement measure vector aver 1×(R−l) to be 0 in aver (denoted as aver j ). Then the basic algorithm which has the maximum value in aver is removed from ∂ and added to∂.…”

mentioning

confidence: 99%

Defeating Untrustworthy Testing Parties: A Novel Hybrid Clustering Ensemble Based Golden Models-Free Hardware Trojan Detection Method

et al. 2019

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Due to the globalization of the design and fabrication process of integrated circuits (ICs), ICs are becoming vulnerable to hardware Trojans. Most of the existing hardware Trojan detection works assume that the testing stage is trustworthy. However, testing parties may collude with malicious attackers and modify the results of hardware Trojan detection. In this paper, two attack models for untrustworthy testing parties are formulated. We further propose an adversarial data generation method for untrustworthy testing parties to modify the collected test data. Then, we propose a novel hybrid clustering ensemble method to build a trusted hardware Trojan detection method (clustering ensemble-based hardware Trojan detection method) against untrustworthy testing parties. To alleviate the impact of process variations and noises on hardware Trojan detection in the actual measurement, the unsupervised correlation-based feature selection method is exploited to process the raw test data of ICs for feature selection. The proposed method can eliminate the need of the fabricated golden chips and the simulated golden models. It can also resist the malicious modifications on Trojan detection results introduced by untrustworthy testing parties. Besides, the following problems and questions are also theoretically analyzed and answered: 1) the number of necessary testing parties; 2) the time overhead and the computational overhead of the proposed method; 3) how to choose the basic clustering algorithms (by using a proposed diversity analysis algorithm); and 4) the reason why the proposed clustering ensemble method is superior to the majority voting method. Both the EDA evaluation on ISCAS89 benchmarks and field-programmable gate array evaluation on Trust-HUB benchmarks are performed to evaluate the performance of the proposed method. Experimental results demonstrate that the proposed method can resist malicious modifications robustly and can detect hardware Trojans with high accuracy (up to 93.75%). Meanwhile, the introduced time overhead is small. INDEX TERMS Hardware security, hardware Trojan detection, untrustworthy testing parties, unsupervised learning, clustering ensemble.

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Cybersecurity Systems Modeling: An Automotive System Case Study

McKelvin

2023

Handbook of Model-Based Systems Engineering

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Realizing a security aware triple modular redundancy scheme for robust integrated circuits

Cited by 10 publications

References 15 publications

Using Approximate Circuits Against Hardware Trojans

Using Approximate Circuits Against Hardware Trojans

Defeating Untrustworthy Testing Parties: A Novel Hybrid Clustering Ensemble Based Golden Models-Free Hardware Trojan Detection Method

Cybersecurity Systems Modeling: An Automotive System Case Study

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