A Secure Modular Division Algorithm Embedding with Error Detection and Low-Area ASIC Implementation

Hu, Xiaoting; Qin, Zhongping; Yang, Qifan

doi:10.1007/s11265-019-01481-6

Cited by 2 publications

(12 citation statements)

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“…The contributions of this paper are as follows: 1. This paper extends our work in [40] to present a new secure MD architecture that can not only detect, but also locate, the error. 2.…”

Section: Introductionmentioning

confidence: 62%

“…Considering the reliability of finite field arithmetic, researchers have also developed many fault detection schemes [6,10,[34][35][36][37][38][39][40]. Some scholars [34][35][36] explored deep into concurrent error detection schemes for division/division over the Galois field GF(2 m ).…”

Section: Introductionmentioning

confidence: 99%

“…Focusing on modular division over a prime field, Hu et al [40] came up with a concurrent error detection scheme based on linear arithmetic code (LAC), and applied it to systolic implementation of MD. As shown in Figure 1, the scheme consists of a main function module (MFM) and an error detection module (EDM).…”

Section: Introductionmentioning

confidence: 99%

“…The MD output is regarded as valid, if and only if the actual and predicted check parts of any iteration are equal to each other. On the upside, the scheme in [40] can detect errors accurately with limited area and time overheads. On the downside, this scheme cannot report the detected errors in real-time because it takes the entire n-bit iterative result as the detection cell so that the system cannot output the iterative detection result until the last word of the iteration result is valid.…”

Section: Introductionmentioning

confidence: 99%

“…Inspired by the concurrent error detection scheme for the MD in [40], this paper proposes a novel MD architecture capable of effectively detecting and locating erroneous processing elements, and applicable to related cryptographic implementations, laying the basis for prevention of natural faults and fault attacks. The contributions of this paper are as follows: 1.…”

Section: Introductionmentioning

confidence: 99%

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A Secure Architecture for Modular Division over a Prime Field against Fault Injection Attacks

Qin

2020

Applied Sciences

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Fault injection attacks pose a serious threat to many cryptographic devices. The security of most cryptographic devices hinges on a key block called modular division (MD) over a prime field. Although a lot of research has been done to implement the MD over a prime field in hardware efficiently, studies on secure architecture against fault injection attack are very few. A few of the studies that focused on secure architecture against fault injection attack can only detect faults but not locate faults. In this regard, this paper designs a novel secure architecture for the MD over a prime field, which can not only detect faults, but also can locate the error processing element. In order to seek the best optimal performance, four word-oriented systolic structures of a main function module (MFM) were designed, and three error detection schemes were developed based on different linear arithmetic codes (LACs). The MFM structures were combined flexibly with the error detection schemes. The time and area overheads of our architecture were analyzed through the implementation in an application-specific integrated circuit (ASIC), while the error detection and location capabilities of our architecture were demonstrated by C++ simulation, in comparison to two existing methods. The results show that our architecture can detect single-bit error (SBE) with 100% accuracy and locate the erroneous processing element (PE), and correctly identify most of the single PE errors and almost all of the multi-PE errors (when there are more than three erroneous PEs). The only weakness of our architecture is the relatively high time and area overhead ratios.

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“…The contributions of this paper are as follows: 1. This paper extends our work in [40] to present a new secure MD architecture that can not only detect, but also locate, the error. 2.…”

Section: Introductionmentioning

confidence: 62%