3 research outputs found

    SRAM PUF์˜ ์‹ ๋ขฐ์„ฑ ๊ฐœ์„ ์„ ์œ„ํ•œ ์ „์› ๊ณต๊ธ‰ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(์ง€๋Šฅํ˜•์œตํ•ฉ์‹œ์Šคํ…œ์ „๊ณต), 2021. 2. ์ „๋™์„.PUF (Physically Unclonable Function)์€ ํ•˜๋“œ์›จ์–ด ๋ ˆ๋ฒจ์˜ ์ธ์ฆ ๊ณผ ์ •์—์„œ ๋„๋ฆฌ ์ด์šฉ๋˜๋Š” ๋ฐฉ๋ฒ•์ด๋‹ค. ๊ทธ ์ค‘์—์„œ๋„ SRAM PUF๋Š” ๊ฐ€์žฅ ์ž˜ ์•Œ ๋ ค์ง„ PUF์˜ ๋ฐฉ๋ฒ•๋ก ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•œ ๋™์ž‘์œผ๋กœ ์ธํ•ด ๋ฐœ์ƒ๋˜๋Š” ๋‚ฎ์€ ์žฌ์ƒ์‚ฐ์„ฑ๊ณผ ์ „์› ๊ณต๊ธ‰ ๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋…ธ์ด์ฆˆ์˜ ๋ฌธ์ œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ํšจ๊ณผ์ ์œผ๋กœ SRAM PUF์˜ ์žฌ์ƒ์‚ฐ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๋‘ ๊ฐ€์ง€ ์ „์› ๊ณต๊ธ‰ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์‹œํ•œ ๊ธฐ๋ฒ•๋“ค์€ ๊ฐ’์ด ์‚ฐ์ถœ๋˜ ๋Š” ์˜์—ญ ํ˜น์€ ์ „์› ๊ณต๊ธ‰์›์˜ ๊ธฐ์šธ๊ธฐ(ramp-up ์‹œ๊ฐ„)๋ฅผ ์กฐ์ ˆํ•จ์œผ๋กœ์จ ์› ํ•˜์ง€ ์•Š๋Š” ๋น„ํŠธ์˜ ๋’ค์ง‘ํž˜(flipping) ํ˜„์ƒ์„ ์ค„์ธ๋‹ค. 180nm ๊ณต์ •์œผ๋กœ ์ œ ์ž‘๋œ ํ…Œ์ŠคํŠธ ์นฉ์„ ์ด์šฉํ•œ ์ธก์ • ๊ฒฐ๊ณผ ์žฌ์ƒ์‚ฐ์„ฑ์ด 2.2๋ฐฐ ํ–ฅ์ƒ๋˜์—ˆ์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ NUBs(Native Unstable Bits)๋Š” 54.87% ๊ทธ๋ฆฌ๊ณ  BER (Bit Error Rate)๋Š” 55.05% ๊ฐ์†Œํ•œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.Physically unclonable function (PUF) is a widely used hardware-level identification method. SRAM-based PUFs are the most well-known PUF topology, but they typically suffer from low reproducibility due to non-deterministic behaviors and noise during power-up process. In this work, we propose two power-up control techniques that effectively improve reproducibility of the SRAM PUFs. The techniques reduce undesirable bit flipping during evaluation by controlling either evaluation region or power supply ramp-up speed. Measurement results from the 180 nm test chip confirm that native unstable bits (NUBs) are reduced by 54.87% and bit error rate (BER) decreases by 55.05% while reproducibility increases by 2.2ร—.Chapter 1 Introduction 1 1.1 PUF in Hardware Securit 1 1.2 Prior Works and Motivation 2 Chapter 2 Related works and Motivation 5 2.1 Uniqueness 7 2.2 Reproducibility 7 2.3 Hold Static Noise Margin (SNM) 8 2.4 Bit Error Rate (BER) 9 2.5 PUF Static Noise Margin Ratio (PSNMratio) 9 Chapter 3 Microarchitecture-Aware Code Generation 11 3.1 Scheme 1: Developing Fingerprint in Sub-Threshold Region 13 3.2 Scheme 2: Controlling Voltage Ramp-up Speed 17 Chapter 4 Experimental Evaluation 19 4.1 Experimental Setup 19 4.2 Evaluation Results 21 Chapter 5 Conclusion 28 Bibliography 29 Abstract in Korean 33Maste

    Analysis of Microcontroller Embedded SRAMs for Applications in Physical Unclonable Functions

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    The growth of the Internet of Things (IoT) market has motivated widespread proliferation of microcontroller- (MCU) based embedded systems. Suitable due to their abundance, low cost, low power consumption and small footprint. The memory architecture typically consists of volatile memory such as block(s) of SRAM, and non-volatile memory (NVM) for code storage. Authentication and encryption safeguard these endpoints within an IoT framework, which requires storage of a secure key. Keys stored within integrated circuits (ICs) are susceptible to attack via reverse engineering of the NVM. Newer approaches use Physical Unclonable Functions (PUFs), which produce unique identi ers that takes advantage of device-level randomness induced by manufacturing process variation in silicon. The unclonable property of PUFs is demonstrated with an analytical model. The unpredictable yet repeatable start-up values (SUVs) of SRAM bit-cells form the basis of an SRAM PUF. Performance measures, such as reliability, randomness, symmetry, and stability, dictate the quality of a PUF. Two commercial o -the-shelf (COTS) ARM-Cortex based MCU products, the STM32F429ZIT6U and ATSAMR21G18A, underwent automated and manual power cycling experiments that examined their embedded SRAM SUVs. The characterization framework provided acquires data via debug software and a developed C program, power cycling using a USB controlled relay and post-processing using Python. Applications of PUFs include cryptographic key generation, device identi cation and true random number hardware generation. Statistical results and a comparative analysis are presented. Amongst the total bitcell count of the embedded SRAM in STM and ATSAM MCUs, 36:86% and 28:86% are classi ed as non- or partially-skewed, respectively across N = 10; 000 samples. The Atmel MCU outperforms the STM MCU in reliability by 1.42 %, randomness by 0.65 % and stability by 8.00 %, with a 4.74 % SUV bias towards a logic '1'. Max errors per 128-bit data item is 22 and 38 bits for MCU #1 and MCU #2, respectively. The STM MCU exhibits column-wise correlation illustrated in a heatmap, where the Atmel MCU shows a random signature. The embedded SRAM in the Atmel MCU outperforms the STM MCU's and is thereby considered the more suitable PUF

    ENERGY-EFFICIENT AND SECURE HARDWARE FOR INTERNET OF THINGS (IoT) DEVICES

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    Internet of Things (IoT) is a network of devices that are connected through the Internet to exchange the data for intelligent applications. Though IoT devices provide several advantages to improve the quality of life, they also present challenges related to security. The security issues related to IoT devices include leakage of information through Differential Power Analysis (DPA) based side channel attacks, authentication, piracy, etc. DPA is a type of side-channel attack where the attacker monitors the power consumption of the device to guess the secret key stored in it. There are several countermeasures to overcome DPA attacks. However, most of the existing countermeasures consume high power which makes them not suitable to implement in power constraint devices. IoT devices are battery operated, hence it is important to investigate the methods to design energy-efficient and secure IoT devices not susceptible to DPA attacks. In this research, we have explored the usefulness of a novel computing platform called adiabatic logic, low-leakage FinFET devices and Magnetic Tunnel Junction (MTJ) Logic-in-Memory (LiM) architecture to design energy-efficient and DPA secure hardware. Further, we have also explored the usefulness of adiabatic logic in the design of energy-efficient and reliable Physically Unclonable Function (PUF) circuits to overcome the authentication and piracy issues in IoT devices. Adiabatic logic is a low-power circuit design technique to design energy-efficient hardware. Adiabatic logic has reduced dynamic switching energy loss due to the recycling of charge to the power clock. As the first contribution of this dissertation, we have proposed a novel DPA-resistant adiabatic logic family called Energy-Efficient Secure Positive Feedback Adiabatic Logic (EE-SPFAL). EE-SPFAL based circuits are energy-efficient compared to the conventional CMOS based design because of recycling the charge after every clock cycle. Further, EE-SPFAL based circuits consume uniform power irrespective of input data transition which makes them resilience against DPA attacks. Scaling of CMOS transistors have served the industry for more than 50 years in providing integrated circuits that are denser, and cheaper along with its high performance, and low power. However, scaling of the transistors leads to increase in leakage current. Increase in leakage current reduces the energy-efficiency of the computing circuits,and increases their vulnerability to DPA attack. Hence, it is important to investigate the crypto circuits in low leakage devices such as FinFET to make them energy-efficient and DPA resistant. In this dissertation, we have proposed a novel FinFET based Secure Adiabatic Logic (FinSAL) family. FinSAL based designs utilize the low-leakage FinFET device along with adiabatic logic principles to improve energy-efficiency along with its resistance against DPA attack. Recently, Magnetic Tunnel Junction (MTJ)/CMOS based Logic-in-Memory (LiM) circuits have been explored to design low-power non-volatile hardware. Some of the advantages of MTJ device include non-volatility, near-zero leakage power, high integration density and easy compatibility with CMOS devices. However, the differences in power consumption between the switching of MTJ devices increase the vulnerability of Differential Power Analysis (DPA) based side-channel attack. Further, the MTJ/CMOS hybrid logic circuits which require frequent switching of MTJs are not very energy-efficient due to the significant energy required to switch the MTJ devices. In the third contribution of this dissertation, we have investigated a novel approach of building cryptographic hardware in MTJ/CMOS circuits using Look-Up Table (LUT) based method where the data stored in MTJs are constant during the entire encryption/decryption operation. Currently, high supply voltage is required in both writing and sensing operations of hybrid MTJ/CMOS based LiM circuits which consumes a considerable amount of energy. In order to meet the power budget in low-power devices, it is important to investigate the novel design techniques to design ultra-low-power MTJ/CMOS circuits. In the fourth contribution of this dissertation, we have proposed a novel energy-efficient Secure MTJ/CMOS Logic (SMCL) family. The proposed SMCL logic family consumes uniform power irrespective of data transition in MTJ and more energy-efficient compared to the state-of-art MTJ/ CMOS designs by using charge sharing technique. The other important contribution of this dissertation is the design of reliable Physical Unclonable Function (PUF). Physically Unclonable Function (PUF) are circuits which are used to generate secret keys to avoid the piracy and device authentication problems. However, existing PUFs consume high power and they suffer from the problem of generating unreliable bits. This dissertation have addressed this issue in PUFs by designing a novel adiabatic logic based PUF. The time ramp voltages in adiabatic PUF is utilized to improve the reliability of the PUF along with its energy-efficiency. Reliability of the adiabatic logic based PUF proposed in this dissertation is tested through simulation based temperature variations and supply voltage variations
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