A PUF based Lightweight Hardware Security Architecture for IoT

With an increasing number of hand-held electronics, gadgets, and other smart devices, data is present in a large number of platforms, thereby increasing the risk of security, privacy, and safety breach than ever before. Due to the extreme lightweight nature of these devices, commonly referred to as IoT or `Internet of Things\u27, providing any kind of security is prohibitive due to high overhead associated with any traditional and mathematically robust cryptographic techniques. Therefore, researchers have searched for alternative intuitive solutions for such devices. Hardware security, unlike traditional cryptography, can provide unique device-specific security solutions with little overhead, address vulnerability in hardware and, therefore, are attractive in this domain. As Moore\u27s law is almost at its end, different emerging devices are being explored more by researchers as they present opportunities to build better application-specific devices along with their challenges compared to CMOS technology. In this work, we have proposed emerging nanotechnology-based hardware security as a security solution for resource constrained IoT domain. Specifically, we have built two hardware security primitives i.e. physical unclonable function (PUF) and true random number generator (TRNG) and used these components as part of a security protocol proposed in this work as well. Both PUF and TRNG are built from metal-oxide memristors, an emerging nanoscale device and are generally lightweight compared to their CMOS counterparts in terms of area, power, and delay. Design challenges associated with designing these hardware security primitives and with memristive devices are properly addressed. Finally, a complete security protocol is proposed where all of these different pieces come together to provide a practical, robust, and device-specific security for resource-limited IoT systems

MANAGING AND LEVERAGING VARIATIONS AND NOISE IN NANOMETER CMOS

Advanced CMOS technologies have enabled high density designs at the cost of complex fabrication process. Variation in oxide thickness and Random Dopant Fluctuation (RDF) lead to variation in transistor threshold voltage Vth. Current photo-lithography process used for printing decreasing critical dimensions result in variation in transistor channel length and width. A related challenge in nanometer CMOS is that of on-chip random noise. With decreasing threshold voltage and operating voltage; and increasing operating temperature, CMOS devices are more sensitive to random on-chip noise in advanced technologies. In this thesis, we explore novel circuit techniques to manage the impact of process variation in nanometer CMOS technologies. We also analyze the impact of on-chip noise on CMOS circuits and propose techniques to leverage or manage impact of noise based on the application. True Random Number Generator (TRNG) is an interesting cryptographic primitive that leverages on-chip noise to generate random bits; however, it is highly sensitive to process variation. We explore novel metastability circuits to alleviate the impact of variations and at the same time leverage on-chip noise sources like Random Thermal Noise and Random Telegraph Noise (RTN) to generate high quality random bits. We develop stochastic models for metastability based TRNG circuits to analyze the impact of variation and noise. The stochastic models are used to analyze and compare low power, energy efficient and lightweight post-processing techniques targeted to low power applications like System on Chip (SoC) and RFID. We also propose variation aware circuit calibration techniques to increase reliability. We extended this technique to a more generic application of designing Post-Si Tunable (PST) clock buffers to increase parametric yield in the presence of process variation. Apart from one time variation due to fabrication process, transistors undergo constant change in threshold voltage due to aging/wear-out effects and RTN. Process variation affects conventional sensors and introduces inaccuracies during measurement. We present a lightweight wear-out sensor that is tolerant to process variation and provides a fine grained wear-out sensing. A similar circuit is designed to sense fluctuation in transistor threshold voltage due to RTN. Although thermal noise and RTN are leveraged in applications like TRNG, they affect the stability of sensitive circuits like Static Random Access Memory (SRAM). We analyze the impact of on-chip noise on Bit Error Rate (BER) and post-Si test coverage of SRAM cells

Techniques for Aging, Soft Errors and Temperature to Increase the Reliability of Embedded On-Chip Systems

This thesis investigates the challenge of providing an abstracted, yet sufficiently accurate reliability estimation for embedded on-chip systems. In addition, it also proposes new techniques to increase the reliability of register files within processors against aging effects and soft errors. It also introduces a novel thermal measurement setup that perspicuously captures the infrared images of modern multi-core processors

Characterizing the influence of neutron fields in causing single-event effects using portable detectors

The malfunction of semiconductor devices caused by cosmic rays is known as Single Event Effects(SEEs). In the atmosphere, secondary neutrons are the dominant particles causing this effect. The neutron flux density in atmosphere is very low. For a good statistical certainty, millions of device hours are required to measure the event rate of a device in the natural environment. Event rates obtained in such testings are accurate. To reduce the cost and time of getting the event rate, a device is normally taken to artificial accelerated neutron beams to measure its sensitivity to neutrons. Comparing the flux density of the beam and the flux density of a location in the atmosphere, the real time event rate can be predicted by the event rate obtained. This testing method was standardized as the neutron accelerated soft error rate (ASER) testing in JEDEC JESD89A standard. However, several life testings indicated that the neutron flux density predictions given by the accelerated testings can have large errors. Up to a factor of 2 discrepancy was reported in the literature. One of the major error sources is the equivalence of the absolute neutron flux density in the atmosphere and in accelerated beam. This thesis proposes an alternative accelerated method of predicting the real-time neutron error rate by using proxy devices. This method can avoid the error introduced by the uncertainty in the neutron flux density. The Imaging Single Event Effect Monitor (ISEEM) is one of the proxy devices. It is the instrument originally developed by Z. Török and his co-workers in the University of Central Lancashire. A CCD was used as the sensitive element to detect neutrons. A large amount of data sets acquired by Török were used in this work. A re-engineered ISEEM has been developed in this work to improve ISEEM performance in life testings. Theoretical models have been developed to analyze the response of ISEEM in a wide range of neutron facilities and natural environment. The agreement of the measured and calculated cross-sections are within the error quoted by facilities. Because of the alpha contamination and primary proton direct ionization effects, performance of ISEEM in life testings appeared to be weak

Reliability-aware memory design using advanced reconfiguration mechanisms

Fast and Complex Data Memory systems has become a necessity in modern computational units in today's integrated circuits. These memory systems are integrated in form of large embedded memory for data manipulation and storage. This goal has been achieved by the aggressive scaling of transistor dimensions to few nanometer (nm) sizes, though; such a progress comes with a drawback, making it critical to obtain high yields of the chips. Process variability, due to manufacturing imperfections, along with temporal aging, mainly induced by higher electric fields and temperature, are two of the more significant threats that can no longer be ignored in nano-scale embedded memory circuits, and can have high impact on their robustness. Static Random Access Memory (SRAM) is one of the most used embedded memories; generally implemented with the smallest device dimensions and therefore its robustness can be highly important in nanometer domain design paradigm. Their reliable operation needs to be considered and achieved both in cell and also in architectural SRAM array design. Recently, and with the approach to near/below 10nm design generations, novel non-FET devices such as Memristors are attracting high attention as a possible candidate to replace the conventional memory technologies. In spite of their favorable characteristics such as being low power and highly scalable, they also suffer with reliability challenges, such as process variability and endurance degradation, which needs to be mitigated at device and architectural level. This thesis work tackles such problem of reliability concerns in memories by utilizing advanced reconfiguration techniques. In both SRAM arrays and Memristive crossbar memories novel reconfiguration strategies are considered and analyzed, which can extend the memory lifetime. These techniques include monitoring circuits to check the reliability status of the memory units, and architectural implementations in order to reconfigure the memory system to a more reliable configuration before a fail happens.Actualmente, el diseño de sistemas de memoria en circuitos integrados busca continuamente que sean más rápidos y complejos, lo cual se ha vuelto de gran necesidad para las unidades de computación modernas. Estos sistemas de memoria están integrados en forma de memoria embebida para una mejor manipulación de los datos y de su almacenamiento. Dicho objetivo ha sido conseguido gracias al agresivo escalado de las dimensiones del transistor, el cual está llegando a las dimensiones nanométricas. Ahora bien, tal progreso ha conllevado el inconveniente de una menor fiabilidad, dado que ha sido altamente difícil obtener elevados rendimientos de los chips. La variabilidad de proceso - debido a las imperfecciones de fabricación - junto con la degradación de los dispositivos - principalmente inducido por el elevado campo eléctrico y altas temperaturas - son dos de las más relevantes amenazas que no pueden ni deben ser ignoradas por más tiempo en los circuitos embebidos de memoria, echo que puede tener un elevado impacto en su robusteza final. Static Random Access Memory (SRAM) es una de las celdas de memoria más utilizadas en la actualidad. Generalmente, estas celdas son implementadas con las menores dimensiones de dispositivos, lo que conlleva que el estudio de su robusteza es de gran relevancia en el actual paradigma de diseño en el rango nanométrico. La fiabilidad de sus operaciones necesita ser considerada y conseguida tanto a nivel de celda de memoria como en el diseño de arquitecturas complejas basadas en celdas de memoria SRAM. Actualmente, con el diseño de sistemas basados en dispositivos de 10nm, dispositivos nuevos no-FET tales como los memristores están atrayendo una elevada atención como posibles candidatos para reemplazar las actuales tecnologías de memorias convencionales. A pesar de sus características favorables, tales como el bajo consumo como la alta escabilidad, ellos también padecen de relevantes retos de fiabilidad, como son la variabilidad de proceso y la degradación de la resistencia, la cual necesita ser mitigada tanto a nivel de dispositivo como a nivel arquitectural. Con todo esto, esta tesis doctoral afronta tales problemas de fiabilidad en memorias mediante la utilización de técnicas de reconfiguración avanzada. La consideración de nuevas estrategias de reconfiguración han resultado ser validas tanto para las memorias basadas en celdas SRAM como en `memristive crossbar¿, donde se ha observado una mejora significativa del tiempo de vida en ambos casos. Estas técnicas incluyen circuitos de monitorización para comprobar la fiabilidad de las unidades de memoria, y la implementación arquitectural con el objetivo de reconfigurar los sistemas de memoria hacia una configuración mucho más fiables antes de que el fallo suced

Variability of low frequency fluctuations in sub 45nm CMOS devices-Experiment, modeling and applications

D une part, les fluctuations et le bruit basse fréquence (BF) dans les dispositifs MOS ont été le sujet de recherche intensive durant ces dernières années. Le bruit BF devient une inquiétude majeure pour la réduction continuelle de la dimension des transistors car le bruit 1/f augmente comme l inverse de la surface des transistors. Le bruit BF et les fluctuations en excès pourraient constituer une limitation sérieuse du fonctionnement des circuits analogiques et numériques. Le bruit 1/f est également d'importance primordiale pour les applications de circuit RF où il provoque le bruit de phase dans les oscillateurs ou les multiplexeurs. Le développement des technologies submicroniques CMOS a conduit à l observation d un nouveau type de bruits, i.e. signaux télégraphiques aléatoires (RTS), entrainant de grandes amplitudes de fluctuations à l heure actuelle, qui peuvent compromettre la fonctionnalité des circuits. D'autre part, la variabilité statistique dans les caractéristiques de transistor est l'un des défis principaux pour les prochaines générations technologiques. La connaissance détaillée des sources de variabilité est extrêmement importante pour la conception et la fabrication des dispositifs résistants à la variabilité. On constate que la dispersion des valeurs de courant de drain des dispositifs n-MOS plutôt petits de la technologie 28 nm est presque deux décades. Cela résulte de l'impact des dopants aléatoires, de la rugosité de bord des lignes et les variations d'épaisseur d'oxyde, qui est plutôt bien compris, ainsi que du rôle du matériau de grille, en poly silicium ou en métal seulement, qui n a été que récemment étudié dans les simulations. La confirmation et la quantification expérimentales de la contribution du bruit et des fluctuations BF manquent toujours. En outre, l'étude de la variabilité du bruit BF et de sa relation avec les autres facteurs des variations des dispositifs n'a été jamais effectuée. Par conséquent, les défis de recherches et les objectifs de cette thèse sont centrés vers les études des fluctuations basses fréquences et du bruit dans les technologies CMOS 32nm et au-delà. Plus spécifiquement, le bruit BF sera étudié avec trois objectifs : i) la caractérisation détaillée du bruit BF des nouvelles technologies CMOS comportant des grilles avec high-k/métal, des poches de canal etc., ii) le changement des paramètres de bruit BF des différentes technologies et iii) l'impact du bruit BF et des fluctuations RTS en tant que sources de variabilité pour des applications de circuit analogique et numérique. Le premier objectif adressera l'origine des fluctuations de BF dans des dispositifs CMOS en termes de densité de piège et de localisation des défauts dans le diélectrique de grille et avec la longueur du canal pour différentes architectures (poche, canal de germanium, FD-SOI etc.). La deuxième partie considérera la variabilité du bruit BF résultant de la dispersion énorme des sources de bruit de dispositif à dispositif ; ceci sera conduit grâce à des mesures statistiques des caractéristiques de bruit de BF en fonction de la surface des dispositifs et des générations technologiques. Le troisième objective se concentrera sur l'impact du bruit de BF ou des fluctuations RTS sur le fonctionnement des circuits élémentaires (inverseur, cellule SRAM) et considérés en tant que source temporelle de variabilité. Nous allons aborder ces trois questions une après l autre dans les paragraphes suivants.Low frequency (LF) noise and fluctuations in MOS devices has been the subject of intensive research during the past years. The LF noise is becoming a major concern for continuously scaled down devices, since the 1/f noise increases as the reciprocal of the device area. Excessive low frequency noise and fluctuations could lead to serious limitation of the functionality of the analog and digital circuits. The 1/f noise is also of paramount importance in RF circuit applications where it gives rise to phase noise in oscillators or multiplexors. The development of submicronic CMOS technologies has led to the onset of new type of noises, i.e. random telegraph signals (RTS), yielding large current fluctuations, which can jeopardize the circuit functionality. However, the statistical variability in the transistor characteristics is one of the major challenges for upcoming technological nodes. The detailed knowledge of variability sources is extremely important for the design and manufacturing of variability resistant devices. Whereas the impact of random dopants, line edge roughness and oxide thickness variations is relatively well understood, the role of the polysilicon or metal gate material has only lately been investigated in simulations and experimental confirmation and quantification of its contribution is still lacking. In addition, the study of LFN variability behavior and maybe its relation with the other factors of device variations has never been done. Therefore, the research challenges and objectives of this thesis are centered towards the studies of low frequency fluctuations and noise in 32 nm CMOS technologies and beyond. More specifically, the objectives of the LF noise investigation is summarized in the following points: i) Detailed LF noise characterization of new CMOS technologies featuring high- metal gate stacks, channel pockets etc, ii) change of LF noise parameters from different technologies and iii) impact of LF noise and RTS fluctuations as a variability sources for analog and digital circuits. The first objective addresses the origin of the LF fluctuations in CMOS devices in terms of trap density and defect localization in the gate dielectric and along the channel for various architectures (pocket, Ge channel, FD-SOI etc). The second objective considers the LF noise variability resulting from huge dispersion of noise sources from device to device; this is conducted owing to statistical measurements of LF noise characteristics as a function of device area and technological splits. The third issue is focused on the impact of LF noise or RTS fluctuations on the operation of elementary circuits (inverter, SRAM cell) regarded as temporal variability source.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Characterisation and modelling of Random Telegraph Noise in nanometre devices

The power consumption of digital circuits is proportional to the square of operation voltage and the demand for low power circuits reduces the operation voltage towards the threshold of MOSFETs. A weak voltage signal makes circuits vulnerable to noise and the optimization of circuit design requires an accurate noise model. RTN is the dominant noise for modern CMOS technologies. This research focuses on the instability induced by Random Telegraph Noise (RTN) in nano-devices for low power applications, such as the Internet of Things (IoT). RTN is a stochastic noise that can be observed in the drain/gate current of a device when traps capture and emit electrons or holes. The impact of RTN instabilities in devices has been widely investigated. Although progress has been made, the understanding of RTN instabilities remains incomplete and many issues are unresolved. This work focuses on developing a statistical model for characterising, modelling and analysing of the impact of RTN on MOSFET performance, as well as to study the prediction for long-term RTN impact on real circuits. As transistor sizes are downscaled, a single trapped charge has a larger impact and RTN becomes increasingly important. To optimize circuit design, one needs to assess the impact of RTN on circuits, which can only be accomplished if there is an accurate statistical model of RTN. The dynamic Monte Carlo modelling requires the statistical distribution functions of both the amplitude and the capture/emission time (CET) of traps. Early works were focused on the amplitude distribution and the experimental data of CETs has been too limited to establish their statistical distribution reliably. In particular, the time window used has often been small, e.g. 10 sec or less, so that there is little data on slow traps. It is not known whether the CET distribution extracted from such a limited time window can be used to predict the RTN beyond the test time window. The first contribution of this work is three-fold: to provide long-term RTN data and use it to test the CET distributions proposed by early works; to propose a methodology for characterising the CET distribution for a fabrication process efficiently; and, for the first time, to verify the long-term prediction capability of a CET distribution beyond the time window used for its extraction. On the statistical distributions of RTN amplitude, three different distributions were proposed by early works: Lognormal, Exponential, and Gumbel distributions. They give substantially different RTN predictions and agreement has not been reached on which distribution should be used, calling the modelling accuracy into question. The second contribution of this work is to assess the accuracy of these three distributions and to explore other distributions for better accuracy. A novel criterion has been proposed for selecting distributions, which requires a monotonic reduction of modelling errors with increasing number of traps. The three existing distributions do not meet this criterion and thirteen other distributions are explored. It is found that the Generalized Extreme Value (GEV) distribution has the lowest error and meets the new criterion. Moreover, to reduce modelling errors, early works used bimodal Lognormal and Exponential distributions, which have more fitting parameters. Their errors, however, are still higher than those of the monomodal GEV distribution. GEV has a long distribution tail and predicts substantially worse RTN impact. The project highlights the uncertainty in predicting the RTN distribution tail by different statistical models. The last contribution of the project is studying the impact of different gate biases on RTN distributions. At two different gate voltage conditions: one close to threshold voltage |Vth| and the other under operating conditions, it is found that the RTN amplitude follows different distributions. At operating voltage condition, Lognormal distribution has the lowest error for RTN amplitude distribution in comparison with other distributions. The amplitude distribution at close to |Vth| has a longer tail compared with the distribution tail at operating voltage. However, RTN capture/emission time distribution is not impacted by gate bias and follows Log-uniform distribution

Characterizing the influence of neutron fields in causing single-event effects using portable detectors

The malfunction of semiconductor devices caused by cosmic rays is known as Single Event Effects(SEEs). In the atmosphere, secondary neutrons are the dominant particles causing this effect. The neutron flux density in atmosphere is very low. For a good statistical certainty, millions of device hours are required to measure the event rate of a device in the natural environment. Event rates obtained in such testings are accurate. To reduce the cost and time of getting the event rate, a device is normally taken to artificial accelerated neutron beams to measure its sensitivity to neutrons. Comparing the flux density of the beam and the flux density of a location in the atmosphere, the real time event rate can be predicted by the event rate obtained. This testing method was standardized as the neutron accelerated soft error rate (ASER) testing in JEDEC JESD89A standard. However, several life testings indicated that the neutron flux density predictions given by the accelerated testings can have large errors. Up to a factor of 2 discrepancy was reported in the literature. One of the major error sources is the equivalence of the absolute neutron flux density in the atmosphere and in accelerated beam. This thesis proposes an alternative accelerated method of predicting the real-time neutron error rate by using proxy devices. This method can avoid the error introduced by the uncertainty in the neutron flux density. The Imaging Single Event Effect Monitor (ISEEM) is one of the proxy devices. It is the instrument originally developed by Z. Török and his co-workers in the University of Central Lancashire. A CCD was used as the sensitive element to detect neutrons. A large amount of data sets acquired by Török were used in this work. A re-engineered ISEEM has been developed in this work to improve ISEEM performance in life testings. Theoretical models have been developed to analyze the response of ISEEM in a wide range of neutron facilities and natural environment. The agreement of the measured and calculated cross-sections are within the error quoted by facilities. Because of the alpha contamination and primary proton direct ionization effects, performance of ISEEM in life testings appeared to be weak.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A statistical study of time dependent reliability degradation of nanoscale MOSFET devices

Charge trapping at the channel interface is a fundamental issue that adversely affects the reliability of metal-oxide semiconductor field effect transistor (MOSFET) devices. This effect represents a new source of statistical variability as these devices enter the nano-scale era. Recently, charge trapping has been identified as the dominant phenomenon leading to both random telegraph noise (RTN) and bias temperature instabilities (BTI). Thus, understanding the interplay between reliability and statistical variability in scaled transistors is essential to the implementation of a ‘reliability-aware’ complementary metal oxide semiconductor (CMOS) circuit design. In order to investigate statistical reliability issues, a methodology based on a simulation flow has been developed in this thesis that allows a comprehensive and multi-scale study of charge-trapping phenomena and their impact on transistor and circuit performance. The proposed methodology is accomplished by using the Gold Standard Simulations (GSS) technology computer-aided design (TCAD)-based design tool chain co-optimization (DTCO) tool chain. The 70 nm bulk IMEC MOSFET and the 22 nm Intel fin-shape field effect transistor (FinFET) have been selected as targeted devices. The simulation flow starts by calibrating the device TCAD simulation decks against experimental measurements. This initial phase allows the identification of the physical structure and the doping distributions in the vertical and lateral directions based on the modulation in the inversion layer’s depth as well as the modulation of short channel effects. The calibration is further refined by taking into account statistical variability to match the statistical distributions of the transistors’ figures of merit obtained by measurements. The TCAD simulation investigation of RTN and BTI phenomena is then carried out in the presence of several sources of statistical variability. The study extends further to circuit simulation level by extracting compact models from the statistical TCAD simulation results. These compact models are collected in libraries, which are then utilised to investigate the impact of the BTI phenomenon, and its interaction with statistical variability, in a six transistor-static random access memory (6T-SRAM) cell. At the circuit level figures of merit, such as the static noise margin (SNM), and their statistical distributions are evaluated. The focus of this thesis is to highlight the importance of accounting for the interaction between statistical variability and statistical reliability in the simulation of advanced CMOS devices and circuits, in order to maintain predictivity and obtain a quantitative agreement with a measured data. The main findings of this thesis can be summarised by the following points: Based on the analysis of the results, the dispersions of VT and ΔVT indicate that a change in device technology must be considered, from the planar MOSFET platform to a new device architecture such as FinFET or SOI. This result is due to the interplay between a single trap charge and statistical variability, which has a significant impact on device operation and intrinsic parameters as transistor dimensions shrink further. The ageing process of transistors can be captured by using the trapped charge density at the interface and observing the VT shift. Moreover, using statistical analysis one can highlight the extreme transistors and their probable effect on the circuit or system operation. The influence of the passgate (PG) transistor in a 6T-SRAM cell gives a different trend of the mean static noise margin