74 research outputs found

    MEMS sensors as physical unclonable functions

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    A fundamental requirement of any crypto system is that secret-key material remains securely stored so that it is robust in withstanding attacks including physical tampering. In this context, physical unclonable functions (PUFs) have been proposed to store cryptographic secrets in a particularly secure manner. In this thesis, the feasibility of using microelectromechanical systems (MEMS) sensors for secure key storage purposes is evaluated for the first time. To this end, we investigated an off-the-shelf 3-axis MEMS gyroscope design and used its properties to derive a unique fingerprint from each sensor. We thoroughly examined the robustness of the derived fingerprints against temperature variation and aging. We extracted stable keys with nearly full entropy from the fingerprints. The security level of the extracted keys lies in a range between 27 bits and 150 bits depending on the applied test conditions and the used entropy estimation method. Moreover, we provide experimental evidence that the extractable key length is higher in practice when multiple wafers are considered. In addition, it is shown that further improvements could be achieved by using more precise measurement techniques and by optimizing the MEMS design. The robustness of a MEMS PUF against tampering and malicious read-outs was tested by three different types of physical attacks. We could show that MEMS PUFs provide a high level of protection due to the sensitivity of their characteristics to disassembly.Eine grundlegende Anforderung jedes Kryptosystems ist, dass der verwendete geheime Schlüssel sicher und geschützt aufbewahrt wird. Vor diesem Hintergrund wurden physikalisch unklonbare Funktionen (PUFs) vorgeschlagen, um kryptographische Geheimnisse besonders sicher zu speichern. In dieser Arbeit wird erstmals die Verwendbarkeit von mikroelektromechanischen Systemen (MEMS) für die sichere Schlüsselspeicherung anhand eines 3-achsigen MEMS Drehratensensor gezeigt. Dabei werden die Eigenschaften der Sensoren zur Ableitung eines eindeutigen Fingerabdrucks verwendet. Die Temperatur- und Langzeitstabilität der abgeleiteten Fingerabdrücke wurde ausführlich untersucht. Aus den Fingerabdrücken wurden stabile Schlüssel mit einem Sicherheitsniveau zwischen 27 Bit und 150 Bit, abhängig von den Testbedingungen und der verwendeten Entropie-Schätzmethode, extrahiert. Außerdem konnte gezeigt werden, dass die Schlüssellänge ansteigt, je mehr Wafer betrachtet werden. Darüber hinaus wurde die Verwendung einer präziseren Messtechnik und eine Optimierung des MEMS-Designs als potentielle Verbesserungsmaßnahmen identifiziert. Die Robustheit einer MEMS PUF gegen Manipulationen und feindseliges Auslesen durch verschiedene Arten von physikalischen Angriffen wurde untersucht. Es konnte gezeigt werden, dass MEMS PUFs aufgrund der Empfindlichkeit ihrer Eigenschaften hinsichtlich einer Öffnung des Mold-Gehäuses eine hohe Widerstandsfähigkeit gegenüber invasiven Angriffen aufweisen

    A Power-Gated 8-Transistor Physically Unclonable Function Accelerates Evaluation Speeds

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    \ua9 2023 by the authors.The proposed 8-Transistor (8T) Physically Unclonable Function (PUF), in conjunction with the power gating technique, can significantly accelerate a single evaluation cycle more than 100,000 times faster than a 6-Transistor (6T) Static Random-Access Memory (SRAM) PUF. The 8T PUF is built to swiftly eliminate data remanence and maximise physical mismatch. Moreover, a two-phase power gating module is devised to provide controllable power on/off cycles for the chosen PUF clusters in order to facilitate fast statistical measurements and curb the in-rush current. The architecture and hardware implementation of the power-gated PUF are developed to accommodate fast multiple evaluations of PUF Responses. The fast speed enables a new data processing method, which coordinates Dark-bit masking and Multiple Temporal Majority Voting (TMV) in different Process, Voltage and Temperature (PVT) corners or during field usage, hence greatly reducing the Bit Error Rate (BER) and the hardware penalty for error correction. The designs are based on the UMC 65 nm technology and aim to tape out an Application-Specific Integrated Circuit (ASIC) chip. Post-layout Monte Carlo (MC) simulations are performed with Cadence, and the extracted PUF Responses are processed with Matlab to evaluate the 8T PUF performance and statistical metrics for subsequent inclusion in PUF Responses, which comprise the novelty of this approach

    Subwavelength Engineering of Silicon Photonic Waveguides

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    The dissertation demonstrates subwavelength engineering of silicon photonic waveguides in the form of two different structures or avenues: (i) a novel ultra-low mode area v-groove waveguide to enhance light-matter interaction; and (ii) a nanoscale sidewall crystalline grating performed as physical unclonable function to achieve hardware and information security. With the advancement of modern technology and modern supply chain throughout the globe, silicon photonics is set to lead the global semiconductor foundries, thanks to its abundance in nature and a mature and well-established industry. Since, the silicon waveguide is the heart of silicon photonics, it can be considered as the core building block of modern integrated photonic systems. Subwavelength structuring of silicon waveguides shows immense promise in a variety of field of study, such as, tailoring electromagnetic near fields, enhancing light-matter interactions, engineering anisotropy and effective medium effects, modal and dispersion engineering, nanoscale sensitivity etc. In this work, we are going to exploit the boundary conditions of modern silicon photonics through subwavelength engineering by means of novel ultra-low mode area v-groove waveguide to answer long-lasting challenges, such as, fabrication of such sophisticated structure while ensuring efficient coupling of light between dissimilar modes. Moreover, physical unclonable function derived from our nanoscale sidewall crystalline gratings should give us a fast and reliable optical security solution with improved information density. This research should enable new avenues of subwavelength engineered silicon photonic waveguide and answer to many unsolved questions of silicon photonics foundries

    Model Building and Security Analysis of PUF-Based Authentication

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    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

    Non-invasive Techniques Towards Recovering Highly Secure Unclonable Cryptographic Keys and Detecting Counterfeit Memory Chips

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    Due to the ubiquitous presence of memory components in all electronic computing systems, memory-based signatures are considered low-cost alternatives to generate unique device identifiers (IDs) and cryptographic keys. On the one hand, this unique device ID can potentially be used to identify major types of device counterfeitings such as remarked, overproduced, and cloned. On the other hand, memory-based cryptographic keys are commercially used in many cryptographic applications such as securing software IP, encrypting key vault, anchoring device root of trust, and device authentication for could services. As memory components generate this signature in runtime rather than storing them in memory, an attacker cannot clone/copy the signature and reuse them in malicious activity. However, to ensure the desired level of security, signatures generated from two different memory chips should be completely random and uncorrelated from each other. Traditionally, memory-based signatures are considered unique and uncorrelated due to the random variation in the manufacturing process. Unfortunately, in previous studies, many deterministic components of the manufacturing process, such as memory architecture, layout, systematic process variation, device package, are ignored. This dissertation shows that these deterministic factors can significantly correlate two memory signatures if those two memory chips share the same manufacturing resources (i.e., manufacturing facility, specification set, design file, etc.). We demonstrate that this signature correlation can be used to detect major counterfeit types in a non-invasive and low-cost manner. Furthermore, we use this signature correlation as side-channel information to attack memory-based cryptographic keys. We validate our contribution by collecting data from several commercially available off-the-shelf (COTS) memory chips/modules and considering different usage-case scenarios
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