Emerging Physical Unclonable Functions With Nanotechnology

Gao, Yansong; Ranasinghe, Damith C.; Al-Sarawi, Said F.; Kavehei, Omid; Abbott, Derek

doi:10.1109/access.2015.2503432

Cited by 156 publications

(93 citation statements)

References 91 publications

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“…[23][24][25] PUFs provide a unique hardware ID (similar to fingerprints and retinas for humans) for protected hardware systems. [38] Strong PUFs usually have a large number of CRPs by reusing the hardware units. [26,27] Electronic PUFs can be divided into analog PUFs, [22,[28][29][30] delay-based PUFs, [31,32] and memory-based PUFs, [33][34][35][36][37] as shown in Figure 1a.…”

Section: Pufs and Trngsmentioning

confidence: 99%

Memristors for Hardware Security Applications

Pang

Gao

Lin

et al. 2019

Adv Elect Materials

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Memristors have recently been explored for hardware security applications such as true random number generators (TRNGs) and physical unclonable functions (PUFs). Several typical designs for memristor‐based PUFs and TRNGs are summarized. PUFs are a novel hardware security primitive utilizing the intrinsic randomness of a physical system, and PUFs have broad potential applications in key protection and authentication. Unlike most conventional PUFs based on manufacturing variations, memristors have both manufacturing variations and intrinsic randomness in their resistance‐switching mechanisms that can be utilized as entropy sources; for instance, device to device (D2D) variation and probabilistic switching behaviors. TRNGs are a cornerstone of hardware security and are widely used in secure chips and encryption protocols. Memristors have random telegraph noise (RTN) and cycle to cycle (C2C) variation characteristics that can be used for high‐quality TRNGs. Here, research progress in memristor‐based PUFs and TRNGs is reviewed, and how these sources of randomness are leveraged to generate security primitives is discussed.

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Section: Pufs and Trngsmentioning

confidence: 99%

Memristors for Hardware Security Applications

Pang

Gao

Lin

et al. 2019

Adv Elect Materials

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“…In addition to authentication, PUFs can be employed for secure storing. New directives on PUFs can be found in [48,59,88,100,153].…”

Section: • Device Authenticationmentioning

confidence: 99%

Security Considerations for Internet of Things: A Survey

et al. 2020

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Interconnecting "things" and devices that takes the form of wearables, sensors, actuators, mobiles, computers, meters, or even vehicles is a critical requirement for the current era. These inter-networked connections are serving the emerging applications home and building automation, smart cities and infrastructure, smart industries, and smart-everything. However, the security of these connected Internet of things (IoT) plays a centric role with no margin for error. After a review of the relevant, online literature on the topic and after looking at the market trends and developments, one can notice that there are still concerns with regard to security in IoT products and services. This paper is focusing on a survey on IoT security and aims to highlight the most significant problems related to safety and security in the IoT ecosystems. This survey identifies the general threat and attack vectors against IoT devices while highlighting the flaws and weak points that can lead to breaching the security. Furthermore, this paper presents solutions for remediation of the compromised security, as well as methods for risk mitigation, with prevention and improvement suggestions.

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“…There are various silicon PUF constructions that include: delay-based PUF such as Arbiter PUF (APUF) [15], [16] and ring oscillator PUF (ROPUF) [1], [17]- [20]; mismatch based PUFs such as the static random access memory (SRAM) PUF [21], [22], latch PUF [23], flip-flop PUF [24], [25] and Buskeeper PUF [26]; current-based PUF [27], and nonlinear current mirror based PUF [28]. Readers are referred to [29], [30] for details of various PUF constructions.…”

Section: B Sram Pufmentioning

confidence: 99%

Lightweight (Reverse) Fuzzy Extractor With Multiple Reference PUF Responses

Gao

et al. 2019

IEEE Trans.Inform.Forensic Secur.

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A Physical unclonable functions (PUF), alike a fingerprint, exploits manufacturing randomness to endow each physical item with a unique identifier. One primary PUF application is the secure derivation of volatile cryptographic keys using a fuzzy extractor comprising of two procedures: i) secure sketch; and ii) entropy extraction. Although the entropy extractor can be lightweight, the overhead of the secure sketch responsible correcting naturally noisy PUF responses is usually costly. We observe that, in general, response unreliability with respect to a enrolled reference measurement increases with increasing differences between the in-the-field PUF operating condition and the operating condition used in evaluating the enrolled reference response. For the first time, we exploit such an important but inadvertent observation. In contrast to the conventional single reference response enrollment, we propose enrolling multiple reference responses (MRR) subject to the same challenge but under multiple distinct operating conditions. The critical observation here is that one of the reference operating conditions is likely to be closer to the operating condition of the field deployed PUF, thus, resulting in minimizing the expected unreliability when compared to the single reference under the nominal condition. Overall, MRR greatly reduces the demand for the expected number of erroneous bits for correction and, subsequently, achieve a significant reduction in the error correction overhead. The significant implementation efficiency gains from the proposed MRR method is demonstrated from software implementations of fuzzy extractors on batteryless resource constraint computational radio frequency identification devices, where realistic PUF data is collected from the embedded intrinsic SRAM PUFs.

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Emerging Physical Unclonable Functions With Nanotechnology

Cited by 156 publications

References 91 publications

Memristors for Hardware Security Applications

Memristors for Hardware Security Applications

Security Considerations for Internet of Things: A Survey

Lightweight (Reverse) Fuzzy Extractor With Multiple Reference PUF Responses

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