A Robust Authentication Methodology using Physically Unclonable Functions in DRAM Arrays

Hashemian, Maryam S.; Singh, Bhanu Pratap; Wolff, Francis; Weyer, Daniel; Clay, Steve; Papachristou, C.

doi:10.7873/date.2015.0308

Cited by 40 publications

(39 citation statements)

References 24 publications

(41 reference statements)

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“…The Row Hammer PUF, like most memory-based PUF implementations, is an intrinsic PUF and, therefore, its implementation does not require the addition of extra circuitry either for its construction or for its operation. Some other well-known memory-based intrinsic PUFs include the SRAM PUF [37,38], the Flash PUF [39] and different types of DRAM PUFs based either on the startup values of the DRAM cells [15,16] or on their retention times [10][11][12]17] or on the access latency times of the DRAM operations [19,20]. Intrinsic PUFs act as inherent security primitives and can, therefore, be used to enhance the security of low-end devices, such as IoT hardware, that usually cannot support other more demanding security mechanisms, such as a Trusted Platform Module (TPM), due to their limited resources.…”

Section: Memory-based Intrinsic Pufsmentioning

confidence: 99%

“…DRAM-based PUFs are a relatively new category of memory-based PUFs, as the first relevant publications appeared in 2012 [10][11][12][13]. In particular, there are multiple categories of DRAM-based PUFs, each of which takes advantage of a different physical characteristic of the DRAM [14], such as the startup values of the DRAM cells [15,16], their retention times [17,18] and their access latency regarding both the relevant write and read operations [19,20]. In this paper, we focus rather on DRAM PUFs based on the retention times of the DRAM cells, in the presence of the row hammer effect in them.…”

Section: Introductionmentioning

confidence: 99%

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Intrinsic Run-Time Row Hammer PUFs: Leveraging the Row Hammer Effect for Run-Time Cryptography and Improved Security †

et al. 2018

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Physical Unclonable Functions (PUFs) based on the retention times of the cells of a Dynamic Random Access Memory (DRAM) can be utilised for the implementation of cost-efficient and lightweight cryptographic protocols. However, as recent work has demonstrated, the times needed in order to generate their responses may prohibit their widespread usage. To address this issue, the Row Hammer PUF has been proposed by Schaller et al., which leverages the row hammer effect in DRAM modules to reduce the retention times of their cells and, therefore, significantly speed up the generation times for the responses of PUFs based on these retention times. In this work, we extend the work of Schaller et al. by presenting a run-time accessible implementation of this PUF and by further reducing the time required for the generation of its responses. Additionally, we also provide a more thorough investigation of the effects of temperature variations on the Row Hammer PUF and briefly discuss potential statistical relationships between the cells used to implement it. As our results prove, the Row Hammer PUF could potentially provide an adequate level of security for Commercial Off-The-Shelf (COTS) devices, if its dependency on temperature is mitigated, and, may therefore, be commercially adopted in the near future.

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Section: Memory-based Intrinsic Pufsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intrinsic Run-Time Row Hammer PUFs: Leveraging the Row Hammer Effect for Run-Time Cryptography and Improved Security †

et al. 2018

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“…Random number generators can be broadly classi ed into two categories [32,78,145,148]: 1) pseudo-random number generators (PRNGs) [18,98,100,102,133], which deterministically generate numbers starting from a seed value with the goal of approximating a true random sequence, and 2) true random number generators (TRNGs) [6,16,22,23,24,33,36,47,50,55,56,57,65,77,83,96,101,111,116,119,141,143,144,146,149,151,153,155,158], which generate random numbers based on sampling non-deterministic random variables inherent in various physical phenomena (e.g., electrical noise, atmospheric noise, clock jitter, Brownian motion).…”

Section: Introductionmentioning

confidence: 99%

D-RaNGe: Using Commodity DRAM Devices to Generate True Random Numbers with Low Latency and High Throughput

Kim

Patel

Hassan

et al. 2019

2019 IEEE International Symposium on High Performance Computer Architecture (HPCA)

105

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We propose a new DRAM-based true random number generator (TRNG) that leverages DRAM cells as an entropy source.The key idea is to intentionally violate the DRAM access timing parameters and use the resulting errors as the source of randomness. Our technique speci cally decreases the DRAM row activation latency (timing parameter t RCD ) below manufacturerrecommended speci cations, to induce read errors, or activation failures, that exhibit true random behavior. We then aggregate the resulting data from multiple cells to obtain a TRNG capable of providing a high throughput of random numbers at low latency.To demonstrate that our TRNG design is viable using commodity DRAM chips, we rigorously characterize the behavior of activation failures in 282 state-of-the-art LPDDR4 devices from three major DRAM manufacturers. We verify our observations using four additional DDR3 DRAM devices from the same manufacturers. Our results show that many cells in each device produce random data that remains robust over both time and temperature variation. We use our observations to develop D-RaNGe, a methodology for extracting true random numbers from commodity DRAM devices with high throughput and low latency by deliberately violating the read access timing parameters. We evaluate the quality of our TRNG using the commonly-used NIST statistical test suite for randomness and nd that D-RaNGe: 1) successfully passes each test, and 2) generates true random numbers with over two orders of magnitude higher throughput than the previous highest-throughput DRAM-based TRNG.

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“…Moreover, another characteristic of DRAM cells that has been exploited for the implementation of security primitives is the time required for the read and write operations to be successful [20,21]. If this time is decreased, some cells will fail to be read or written, while others will still be read or written successfully, depending on slight variations in their transistors and capacitors.…”

Section: Memory Arraymentioning

confidence: 99%

An Overview of DRAM-Based Security Primitives

et al. 2018

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Recent developments have increased the demand for adequate security solutions, based on primitives that cannot be easily manipulated or altered, such as hardware-based primitives. Security primitives based on Dynamic Random Access Memory (DRAM) can provide cost-efficient and practical security solutions, especially for resource-constrained devices, such as hardware used in the Internet of Things (IoT), as DRAMs are an intrinsic part of most contemporary computer systems. In this work, we present a comprehensive overview of the literature regarding DRAM-based security primitives and an extended classification of it, based on a number of different criteria. In particular, first, we demonstrate the way in which DRAMs work and present the characteristics being exploited for the implementation of security primitives. Then, we introduce the primitives that can be implemented using DRAM, namely Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs), and present the applications of each of the two types of DRAM-based security primitives. We additionally proceed to assess the security such primitives can provide, by discussing potential attacks and defences, as well as the proposed security metrics. Subsequently, we also compare these primitives to other hardware-based security primitives, noting their advantages and shortcomings, and proceed to demonstrate their potential for commercial adoption. Finally, we analyse our classification methodology, by reviewing the criteria employed in our classification and examining their significance.

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A Robust Authentication Methodology using Physically Unclonable Functions in DRAM Arrays

Abstract: We also certify that written approval has been obtained for any proprietary material contained therein.

Cited by 40 publications

References 24 publications

Intrinsic Run-Time Row Hammer PUFs: Leveraging the Row Hammer Effect for Run-Time Cryptography and Improved Security †

Intrinsic Run-Time Row Hammer PUFs: Leveraging the Row Hammer Effect for Run-Time Cryptography and Improved Security †

D-RaNGe: Using Commodity DRAM Devices to Generate True Random Numbers with Low Latency and High Throughput

An Overview of DRAM-Based Security Primitives

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