Improving the Statistical Variability of Delay-based Physical Unclonable Functions

Capovilla, Jefferson; Côrtes, Mário Lúcio; Araújo, Guido

doi:10.1145/2800986.2801010

Cited by 11 publications

(2 citation statements)

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“…www.ijacsa.thesai.org Table 1, the defense mechanisms that were proposed can be divided into three categories namely design, obfuscation and access control. The design category consists of adding non-linearity using XOR logics [6], [7], configuring transistor's gate sizes [62], augmenting interconnects [63], tightening the layout condition [8], exploiting FPGA resources and reconfigurability [9], [10] and modify current PUF design blocks by using analog blocks [11] and reducing feed-forward stages [64]. These defense mechanisms provide resistance to machine learning modeling attacks however they come with certain shortcomings.…”

Section: Comparison Analysis Of Defense Mechanisms Against Attacksmentioning

confidence: 99%

Defense Mechanisms against Machine Learning Modeling Attacks on Strong Physical Unclonable Functions for IOT Authentication: A Review

Noor¹,

Daud²,

Ahmad³

et al. 2017

ijacsa

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Abstract-Security component in IoT system are very crucial because the devices within the IoT system are exposed to numerous malicious attacks. Typical security components in IoT system performs authentication, authorization, message and content integrity check. Regarding authentication, it is normally performed using classical authentication scheme using crypto module. However, the utilization of the crypto module in IoT authentication is not feasible because of the distributed nature of the IoT system which complicates the message cipher and decipher process. Thus, the Physical Unclonable Function (PUF) is suggested to replace crypto module for IoT authentication because it only utilizes responses from set of challenges instead of cryptographic keys to authenticate devices. PUF can generate large number of challenge-response pairs (CRPs) which is good for authentication because the unpredictability is high. However, with the emergence of machine learning modeling, the CRPs now can be predicted through machine learning algorithms. Various defense mechanisms were proposed to counter machine learning modeling attacks (ML-MA). Although they were experimentally proven to be able to increase resiliency against ML-MA, they caused the generated responses to be instable and incurred high area overhead. Thus, there is a need to design the best defense mechanism which is not only resistant to ML-MA but also produces reliable responses and reduces area overhead. This paper presents an analysis on defense mechanisms against ML-MA on strong PUFs for IoT authentication.

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Section: Comparison Analysis Of Defense Mechanisms Against Attacksmentioning

confidence: 99%

Defense Mechanisms against Machine Learning Modeling Attacks on Strong Physical Unclonable Functions for IOT Authentication: A Review

Noor¹,

Daud²,

Ahmad³

et al. 2017

ijacsa

View full text Add to dashboard Cite

show abstract

“…Reliability represents the stability of the response of a PUF design over different environmental conditions. The effect of the selection of arbitrator elements and gate sizes on APUF delay variations has been analyzed in [5]. However, the underlying parameters were regarded as fixed values, and adjustments were needed at higher levels.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Analysis of Delay-Based PUFs and Design Strategies for Improvement

Wang

et al. 2019

2019 IEEE International Symposium on Circuits and Systems (ISCAS)

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Delay-based physical unclonable function (PUF) designs use the random delay differences in circuit transmission to extract response. In the existing PUF designs, there are few studies on investigating the link between process variation and PUF performance. The experimental data can reflect the performance of the new design to a certain extent, but lack of theoretical analysis to provide thorough information. In this paper, a theoretical model for delay-based PUF designs is proposed. An analysis of the delay-based PUF improvements by existing design strategies is also investigated. Moreover, a guidance to develop and improve future delay-based PUF designs using the proposed theoretical model is also given in this paper.

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