物理複製不能関数における安全性の評価と向上に関する研究

In this thesis, we focus on Physically Unclonable Functions (PUFs), which are expected as one of the most promising cryptographic primitives for secure chip authentication. Generally, PUFbased authentication is achieved by two approaches: (A) using a PUF itself, which has multiple challenge (input) and response (output) pairs, or (B) using a cryptographic function, the secret key of which is generated from a PUF with a single challenge-response pair (CRP). We contribute to:(1) evaluate the security of Approach (A), and (2) improve the security of Approach (B). (1) Arbiter-based PUFs were the most feasible type of PUFs, which was used to construct Approach (A). However, Arbiter-based PUFs have a vulnerability; if an attacker knows some CRPs, she/he can predict the remaining unknown CRPs with high probability. Bistable Ring PUF (BR-PUF) was proposed as an alternative, but has not been evaluated by third parties. In this thesis, in order to construct Approach (A) securely, we evaluate the difficulty of predicting responses of a BR-PUF experimentally. As a result, the same responses are frequently generated for two challenges with small Hamming distance. Also, particular bits of challenges have a great impact on the responses. In conclusion, BR-PUFs are not suitable for achieving Approach (A)securely. In future work, we should discuss an alternative PUF suitable for secure Approach (A).(2) In order to achieve Approach (B) securely, a secret key ? generated from a PUF response?should have high entropy. We propose a novel method of extracting high entropy from PUF responses. The core idea is to effectively utilize the information on the proportion of ‘1’s including in repeatedly-measured PUF responses. We evaluate its effectiveness by fabricated test chips. As a result, the extracted entropy is about 1.72 times as large as that without the proposed method.Finally, we organize newly gained knowledge in this thesis, and discuss a new application of PUF-based technologies.電気通信大学201

Design and Evaluation of FPGA-based Hybrid Physically Unclonable Functions

A Physically Unclonable Function (PUF) is a new and promising approach to provide security for physical systems and to address the problems associated with traditional approaches. One of the most important performance metrics of a PUF is the randomness of its generated response, which is presented via uniqueness, uniformity, and bit-aliasing. In this study, we implement three known PUF schemes on an FPGA platform, namely SR Latch PUF, Basic RO PUF, and Anderson PUF. We then perform a thorough statistical analysis on their performance. In addition, we propose the idea of the Hybrid PUF structure in which two (or more) sources of randomness are combined in a way to improve randomness. We investigate two methods in combining the sources of randomness and we show that the second one improves the randomness of the response, significantly. For example, in the case of combining the Basic RO PUF and the Anderson PUF, the Hybrid PUF uniqueness is increased nearly 8%, without any pre-processing or post-processing tasks required. Two main categories of applications for PUFs have been introduced and analyzed: authentication and secret key generation. In this study, we introduce another important application for PUFs. In fact, we develop a secret sharing scheme using a PUF to increase the information rate and provide cheater detection capability for the system. We show that, using the proposed method, the information rate of the secret sharing scheme will improve significantly

EFFICIENT HARDWARE PRIMITIVES FOR SECURING LIGHTWEIGHT SYSTEMS

In the era of IoT and ubiquitous computing, the collection and communication of sensitive data is increasingly being handled by lightweight Integrated Circuits. Efficient hardware implementations of crytographic primitives for resource constrained applications have become critical, especially block ciphers which perform fundamental operations such as encryption, decryption, and even hashing. We study the efficiency of block ciphers under different implementation styles. For low latency applications that use unrolled block cipher implementations, we design a glitch filter to reduce energy consumption. For lightweight applications, we design a novel architecture for the widely used AES cipher. The design eliminates inefficiencies in data movement and clock activity, thereby significantly improving energy efficiency over state-of-the-art architectures. Apart from efficiency, vulnerability to implementation attacks are a concern, which we mitigate by our randomization capable lightweight AES architecture. We fabricate our designs in a commercial 16nm FinFET technology and present measured testchip data on energy consumption and side channel resistance. Finally, we address the problem of supply chain security by using image processing techniques to extract fingerprints from surface texture of plastic IC packages for IC authentication and counterfeit prevention. Collectively these works present efficient and cost effective solutions to secure lightweight systems

Model Building and Security Analysis of PUF-Based Authentication

In the context of hardware systems, authentication refers to the process of confirming the identity and authenticity of chip, board and system components such as RFID tags, smart cards and remote sensors. The ability of physical unclonable functions (PUF) to provide bitstrings unique to each component can be leveraged as an authentication mechanism to detect tamper, impersonation and substitution of such components. However, authentication requires a strong PUF, i.e., one capable of producing a large, unique set of bits per device, and, unlike secret key generation for encryption, has additional challenges that relate to machine learning attacks, protocol attacks and constraints on device resources. We describe the requirements for PUF-based authentication, and present a PUF primitive and protocol designed for authentication in resource constrained devices. Our experimental results are derived from a 28 nm Xilinx FPGA. In the authentication scenario, strong PUFs are required since the adversary could collect a subset of challenges and response pairsto build a model and predict the responses for unseen challenges. Therefore, strong PUFs need to provide exponentially large challenge space and be resilient to model building attacks. We investigate the security properties of a Hardware-embedded Delay PUF called HELP which leverages within-die variations in path delays within a hardware-implemented macro (functional unit) as the entropy source. Several features of the HELP processing engine significantly improve its resistance to model-building attacks. We also investigate a novel technique that significantly improves the statistically quality of the generated bitstring for HELP. Stability across environmental variations such as temperature and voltage, is critically important for Physically Unclonable Functions (PUFs). Nearly all existing PUF systems to date need a mechanism to deal with “bit flips” when exact regeneration of the bitstring is required, e.g., for cryptographic applications. Error correction (ECC) and error avoidance schemes have been proposed but both of these require helper data to be stored for the regeneration process. Unfortunately, helper data adds time and area overhead to the PUF system and provides opportunities for adversaries to reverse engineer the secret bitstring. We propose a non-volatile memory-based (NVM) PUF that is able to avoid bit flips without requiring any type of helper data. We describe the technique in the context of emerging nano-devices, in particular, resistive random access memory (Memristor) cells, but the methodology is applicable to any type of NVM including Flash

A hardware-embedded, delay-based PUF engine designed for use in cryptographic and authentication applications

Cryptographic and authentication applications in application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs), as well as codes for the activation of on-chip features, require the use of embedded secret information. The generation of secret bitstrings using physical unclonable functions, or PUFs, provides several distinct advantages over conventional methods, including the elimination of costly non-volatile memory, and the potential to increase the random bits available to applications. In this dissertation, a Hardware-Embedded Delay PUF (HELP) is proposed that is designed to leverage path delay variations that occur in the core logic macros of a chip to create random bitstrings. A thorough discussion is provided of the operational details of an embedded path timing structure called REBEL that is used by HELP to provide the timing functionality upon which HELP relies for the entropy source for the cryptographic quality of the bitstrings. Further details of the FPGA-based implementation used to prove the viability of the HELP PUF concept are included, along with a discussion of the evolution of the techniques employed in realizing the final PUF engine design. The bitstrings produced by a set of 30 FPGA boards are evaluated with regard to several statistical quality metrics including uniqueness, randomness, and stability. The stability characteristics of the bitstrings are evaluated by subjecting the FPGAs to commercial-grade temperature and power supply voltage variations. In particular, this work evaluates the reproducibility of the bitstrings generated at 0C, 25C, and 70C, and 10% of the rated supply voltage. A pair of error avoidance schemes are proposed and presented that provide significant improvements to the HELP PUF\u27s resiliency against bit-flip errors in the bitstrings

Utilizing the Digital Fingerprint Method for Secure Key Generation

This research examines a new way to generate an uncloneable secure key by taking advantage of the delay characteristics of individual transistors. The user profiles the circuit to deduce the glitch count of each output line for each number of selectable buffers added to the circuit. The user can then use this information to generate a specific glitch count on each output line, which is passed to an encryption algorithm as its key. The results detail tests of two configurations for adding a selectable amount of buffers into each glitch circuit in order to induce additional delay. One configuration adds up to seven buffers that is equivalent to the binary digits used on the three SELECT lines of a multiplexer. The second, referred to as the cascaded design, has eight different quantities of selectable buffers, but they all connect to one multiplexer. Each successive line connects to the previous line and adds a certain number of buffers. The linear selection implementation produces almost 15% more usable output lines over the cascaded design, where a usable line is defined as one that has at least one ‘1’ and one ‘0’ glitch count in response to every buffer count. Tests were also performed to determine the optimal number of buffers added to each output using the linear buffer selection configuration. Using three input bits to the buffer unit produced 30.94% usable outputs. Four bits generated nearly 25% more usable outputs, while the use of six bits gave less than a 5% improvement over four bits. The average repeatability of the glitch count is 94.85% using this method. The overall distinguishability of the generated glitch counts for each output line is 10.46%

Within-Die Delay Variation Measurement And Analysis For Emerging Technologies Using An Embedded Test Structure

Both random and systematic within-die process variations (PV) are growing more severe with shrinking geometries and increasing die size. Escalation in the variations in delay and power with reductions in feature size places higher demands on the accuracy of variation models. Their availability can be used to improve yield, and the corresponding profitability and product quality of the fabricated integrated circuits (ICs). Sources of within-die variations include optical source limitations, and layout-based systematic effects (pitch, line-width variability, and microscopic etch loading). Unfortunately, accurate models of within-die PVs are becoming more difficult to derive because of their increasingly sensitivity to design-context. Embedded test structures (ETS) continue to play an important role in the development of models of PVs and as a mechanism to improve correlations between hardware and models. Variations in path delays are increasing with scaling, and are increasingly affected by neighborhood\u27 interactions. In order to fully characterize within-die variations, delays must be measured in the context of actual core-logic macros. Doing so requires the use of an embedded test structure, as opposed to traditional scribe line test structures such as ring oscillators (RO). Accurate measurements of within-die variations can be used, e.g., to better tune models to actual hardware (model-to-hardware correlations). In this research project, I propose an embedded test structure called REBEL (Regional dELay BEhavior) that is designed to measure path delays in a minimally invasive fashion; and its architecture measures the path delays more accurately. Design for manufacture-ability (DFM) analysis is done on the on 90 nm ASIC chips and 28nm Zynq 7000 series FPGA boards. I present ASIC results on within-die path delay variations in a floating-point unit (FPU) fabricated in IBM\u27s 90 nm technology, with 5 pipeline stages, used as a test vehicle in chip experiments carried out at nine different temperature/voltage (TV) corners. Also experimental data has been analyzed for path delay variations in short vs long paths. FPGA results on within-die variation and die-to-die variations on Advanced Encryption System (AES) using single pipelined stage are also presented. Other analysis that have been performed on the calibrated path delays are Flip Flop propagation delays for both rising and falling edge (tpHL and tpLH), uncertainty analysis, path distribution analysis, short versus long path variations and mid-length path within-die variation. I also analyze the impact on delay when the chips are subjected to industrial-level temperature and voltage variations. From the experimental results, it has been established that the proposed REBEL provides capabilities similar to an off-chip logic analyzer, i.e., it is able to capture the temporal behavior of the signal over time, including any static and dynamic hazards that may occur on the tested path. The ASIC results further show that path delays are correlated to the launch-capture (LC) interval used to time them. Therefore, calibration as proposed in this work must be carried out in order to obtain an accurate analysis of within-die variations. Results on ASIC chips show that short paths can vary up to 35% on average, while long paths vary up to 20% at nominal temperature and voltage. A similar trend occurs for within-die variations of mid-length paths where magnitudes reduced to 20% and 5%, respectively. The magnitude of delay variations in both these analyses increase as temperature and voltage are changed to increase performance. The high level of within-die delay variations are undesirable from a design perspective, but they represent a rich source of entropy for applications that make use of \u27secrets\u27 such as authentication, hardware metering and encryption. Physical unclonable functions (PUFs) are a class of primitives that leverage within-die-variations as a means of generating random bit strings for these types of applications, including hardware security and trust. Zynq FPGAs Die-to-Die and within-die variation study shows that on average there is 5% of within-Die variation and the range of die-to-Die variation can go upto 3ns. The die-to-Die variations can be explored in much further detail to study the variations spatial dependance. Additionally, I also carried out research in the area data mining to cater for big data by focusing the work on decision tree classification (DTC) to speed-up the classification step in hardware implementation. For this purpose, I devised a pipelined architecture for the implementation of axis parallel binary decision tree classification for meeting up with the requirements of execution time and minimal resource usage in terms of area. The motivation for this work is that analyzing larger data-sets have created abundant opportunities for algorithmic and architectural developments, and data-mining innovations, thus creating a great demand for faster execution of these algorithms, leading towards improving execution time and resource utilization. Decision trees (DT) have since been implemented in software programs. Though, the software implementation of DTC is highly accurate, the execution times and the resource utilization still require improvement to meet the computational demands in the ever growing industry. On the other hand, hardware implementation of DT has not been thoroughly investigated or reported in detail. Therefore, I propose a hardware acceleration of pipelined architecture that incorporates the parallel approach in acquiring the data by having parallel engines working on different partitions of data independently. Also, each engine is processing the data in a pipelined fashion to utilize the resources more efficiently and reduce the time for processing all the data records/tuples. Experimental results show that our proposed hardware acceleration of classification algorithms has increased throughput, by reducing the number of clock cycles required to process the data and generate the results, and it requires minimal resources hence it is area efficient. This architecture also enables algorithms to scale with increasingly large and complex data sets. We developed the DTC algorithm in detail and explored techniques for adapting it to a hardware implementation successfully. This system is 3.5 times faster than the existing hardware implementation of classification.\u2

Analysis of Microcontroller Embedded SRAMs for Applications in Physical Unclonable Functions

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

Embedded Systems Security: On EM Fault Injection on RISC-V and BR/TBR PUF Design on FPGA

With the increased usage of embedded computers in modern life and the rapid growth of the Internet of Things (IoT), embedded systems security has become a real concern. Especially with safety-critical systems or devices that communicate sensitive data, security becomes a critical issue. Embedded computers more than others are vulnerable to hardware attacks that target the chips themselves to extract the cryptographic keys, compromise their security, or counterfeit them. In this thesis, embedded security is studied through two different areas. The first is the study of hardware attacks by investigating Electro Magnetic Fault Injection (EMFI) on a RISC-V processor. And the second is the study of the countermeasures against counterfeiting and key extraction by investigating the implementation of the Bistable Ring Physical Unclonable Function (BR-PUF) and its variant the TBR-PUF on FPGA. The experiments on a 320 MHz five-stage pipeline RISC-V core showed that with the increase of frequency and the decrease of supplied voltage, the processor becomes more susceptible to EMFI. Analysis of the effect of EMFI on different types of instructions including arithmetic and logic operations, memory operations, and flow control operations showed different types of faults including instruction skips, instructions corruption, faulted branches, and exception faults with variant probabilities. More interestingly and for the first time, multiple consecutive instructions (up to six instructions) were empirically shown to be faulted at once, which can be very devastating, compromising the effect of software countermeasures such as instruction duplication or triplication. This research also studies the hardware implementation of the BR and TBR PUFs on a Spartan-6 FPGA. A comparative study on both the automatic and manual placement implementation approaches on FPGA is presented. With the use of the settling time as a randomization source for the automatic placement, this approach showed a potential to generate PUFs with good characteristics through multiple trials. The automatic placement approach was successful in generating 4-input XOR BR and TBR PUFs with almost ideal characteristics. Moreover, optimizations on the architectural and layout levels were performed on the BR and TBR PUFs to reduce their footprint on FPGA. This research aims to advance the understanding of the EMFI effect on processors, so that countermeasures may be designed for future secure processors. Additionally, this research helps to advance the understanding of how best to design improved BR and TBR PUFs for key protection in future secure devices