A novel knowledge discovery based approach for supplier risk scoring with application in the HVAC industry

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThis research has led to a novel methodology for assessment and quantification of supply risks in the supply chain. The research has built on advanced Knowledge Discovery techniques and has resulted to a software implementation to be able to do so. The methodology developed and presented here resembles the well-known consumer credit scoring methods as it leads to a similar metric, or score, for assessing a supplier’s reliability and risk of conducting business with that supplier. However, the focus is on a wide range of operational metrics rather than just financial, which credit scoring techniques typically focus on. The core of the methodology comprises the application of Knowledge Discovery techniques to extract the likelihood of possible risks from within a range of available datasets. In combination with cross-impact analysis, those datasets are examined for establish the inter-relationships and mutual connections among several factors that are likely contribute to risks associated with particular suppliers. This approach is called conjugation analysis. The resulting parameters become the inputs into a logistic regression which leads to a risk scoring model the outcome of the process is the standardized risk score which is analogous to the well-known consumer risk scoring model, better known as FICO score. The proposed methodology has been applied to an Air Conditioning manufacturing company. Two models have been developed. The first identifies the supply risks based on the data about purchase orders and selected risk factors. With this model the likelihoods of delivery failures, quality failures and cost failures are obtained. The second model built on the first one but also used the actual data about the performance of supplier to identify risks of conducting business with particular suppliers. Its target was to provide quantitative measures of an individual supplier’s risk level. The supplier risk scoring model is tested on the data acquired from the company for its performance analysis. The supplier risk scoring model achieved 86.2% accuracy, while the area under curve (AUC) was 0.863. The AUC curve is much higher than required model’s validity threshold value of 0.5. It represents developed model’s validity and reliability for future data. The numerical studies conducted with real-life datasets have demonstrated the effectiveness of the proposed methodology and system as well as its future potential for industrial adoption

Design, Fabrication, and Run-time Strategies for Hardware-Assisted Security

Today, electronic computing devices are critically involved in our daily lives, basic infrastructure, and national defense systems. With the growing number of threats against them, hardware-based security features offer the best chance for building secure and trustworthy cyber systems. In this dissertation, we investigate ways of making hardware-based security into a reality with primary focus on two areas: Hardware Trojan Detection and Physically Unclonable Functions (PUFs). Hardware Trojans are malicious modifications made to original IC designs or layouts that can jeopardize the integrity of hardware and software platforms. Since most modern systems critically depend on ICs, detection of hardware Trojans has garnered significant interest in academia, industry, as well as governmental agencies. The majority of existing detection schemes focus on test-time because of the limited hardware resources available at run-time. In this dissertation, we explore innovative run-time solutions that utilize on-chip thermal sensor measurements and fundamental estimation/detection theory to expose changes in IC power/thermal profile caused by Trojan activation. The proposed solutions are low overhead and also generalizable to many other sensing modalities and problem instances. Simulation results using state-of-the-art tools on publicly available Trojan benchmarks verify that our approaches can detect Trojans quickly and with few false positives. Physically Unclonable Functions (PUFs) are circuits that rely on IC fabrication variations to generate unique signatures for various security applications such as IC authentication, anti-counterfeiting, cryptographic key generation, and tamper resistance. While the existence of variations has been well exploited in PUF design, knowledge of exactly how variations come into existence has largely been ignored. Yet, for several decades the Design-for-Manufacturability (DFM) community has actually investigated the fundamental sources of these variations. Furthermore, since manufacturing variations are often harmful to IC yield, the existing DFM tools have been geared towards suppressing them (counter-intuitive for PUFs). In this dissertation, we make several improvements over current state-of-the-art work in PUFs. First, our approaches exploit existing DFM models to improve PUFs at physical layout and mask generation levels. Second, our proposed algorithms reverse the role of standard DFM tools and extend them towards improving PUF quality without harming non-PUF portions of the IC. Finally, since our approaches occur after design and before fabrication, they are applicable to all types of PUFs and have little overhead in terms of area, power, etc. The innovative and unconventional techniques presented in this dissertation should act as important building blocks for future work in cyber security

Techniques for Improving Security and Trustworthiness of Integrated Circuits

The integrated circuit (IC) development process is becoming increasingly vulnerable to malicious activities because untrusted parties could be involved in this IC development flow. There are four typical problems that impact the security and trustworthiness of ICs used in military, financial, transportation, or other critical systems: (i) Malicious inclusions and alterations, known as hardware Trojans, can be inserted into a design by modifying the design during GDSII development and fabrication. Hardware Trojans in ICs may cause malfunctions, lower the reliability of ICs, leak confidential information to adversaries or even destroy the system under specifically designed conditions. (ii) The number of circuit-related counterfeiting incidents reported by component manufacturers has increased significantly over the past few years with recycled ICs contributing the largest percentage of the total reported counterfeiting incidents. Since these recycled ICs have been used in the field before, the performance and reliability of such ICs has been degraded by aging effects and harsh recycling process. (iii) Reverse engineering (RE) is process of extracting a circuit’s gate-level netlist, and/or inferring its functionality. The RE causes threats to the design because attackers can steal and pirate a design (IP piracy), identify the device technology, or facilitate other hardware attacks. (iv) Traditional tools for uniquely identifying devices are vulnerable to non-invasive or invasive physical attacks. Securing the ID/key is of utmost importance since leakage of even a single device ID/key could be exploited by an adversary to hack other devices or produce pirated devices. In this work, we have developed a series of design and test methodologies to deal with these four challenging issues and thus enhance the security, trustworthiness and reliability of ICs. The techniques proposed in this thesis include: a path delay fingerprinting technique for detection of hardware Trojans, recycled ICs, and other types counterfeit ICs including remarked, overproduced, and cloned ICs with their unique identifiers; a Built-In Self-Authentication (BISA) technique to prevent hardware Trojan insertions by untrusted fabrication facilities; an efficient and secure split manufacturing via Obfuscated Built-In Self-Authentication (OBISA) technique to prevent reverse engineering by untrusted fabrication facilities; and a novel bit selection approach for obtaining the most reliable bits for SRAM-based physical unclonable function (PUF) across environmental conditions and silicon aging effects

ENERGY-EFFICIENT FEATURE EXTRACTION ENGINE AND SECURE CHIP IDENTIFICATION FOR UBIQUITOUS SURVEILLANCE

Ph.DDOCTOR OF PHILOSOPH

Maximizing Crosstalk-Induced Slowdown During Path Delay Test

Capacitive crosstalk between adjacent signal wires in integrated circuits may lead to noise or a speedup or slowdown in signal transitions. These in turn may lead to circuit failure or reduced operating speed. This thesis focuses on generating test patterns to induce crosstalk-induced signal delays, in order to determine whether the circuit can still meet its timing specification. A timing-driven test generator is developed to sensitize multiple aligned aggressors coupled to a delay-sensitive victim path to detect the combination of a delay spot defect and crosstalk-induced slowdown. The framework uses parasitic capacitance information, timing windows and crosstalk-induced delay estimates to screen out unaligned or ineffective aggressors coupled to a victim path, speeding up crosstalk pattern generation. In order to induce maximum crosstalk slowdown along a path, aggressors are prioritized based on their potential delay increase and timing alignment. The test generation engine introduces the concept of alignment-driven path sensitization to generate paths from inputs to coupled aggressor nets that meet timing alignment and direction requirements. By using path delay information obtained from circuit preprocessing, preferred paths can be chosen during aggressor path propagation processes. As the test generator sensitizes aggressors in the presence of victim path necessary assignments, the search space is effectively reduced for aggressor path generation. This helps in reducing the test generation time for aligned aggressors. In addition, two new crosstalk-driven dynamic test compaction algorithms are developed to control the increase in test pattern count. The proposed test generation algorithm is applied to ISCAS85 and ISCAS89 benchmark circuits. SPICE simulation results demonstrate the ability of the alignment-driven test generator to increase crosstalk-induced delays along victim paths

Network-on-Chip

Addresses the Challenges Associated with System-on-Chip Integration Network-on-Chip: The Next Generation of System-on-Chip Integration examines the current issues restricting chip-on-chip communication efficiency, and explores Network-on-chip (NoC), a promising alternative that equips designers with the capability to produce a scalable, reusable, and high-performance communication backbone by allowing for the integration of a large number of cores on a single system-on-chip (SoC). This book provides a basic overview of topics associated with NoC-based design: communication infrastructure design, communication methodology, evaluation framework, and mapping of applications onto NoC. It details the design and evaluation of different proposed NoC structures, low-power techniques, signal integrity and reliability issues, application mapping, testing, and future trends. Utilizing examples of chips that have been implemented in industry and academia, this text presents the full architectural design of components verified through implementation in industrial CAD tools. It describes NoC research and developments, incorporates theoretical proofs strengthening the analysis procedures, and includes algorithms used in NoC design and synthesis. In addition, it considers other upcoming NoC issues, such as low-power NoC design, signal integrity issues, NoC testing, reconfiguration, synthesis, and 3-D NoC design. This text comprises 12 chapters and covers: The evolution of NoC from SoC—its research and developmental challenges NoC protocols, elaborating flow control, available network topologies, routing mechanisms, fault tolerance, quality-of-service support, and the design of network interfaces The router design strategies followed in NoCs The evaluation mechanism of NoC architectures The application mapping strategies followed in NoCs Low-power design techniques specifically followed in NoCs The signal integrity and reliability issues of NoC The details of NoC testing strategies reported so far The problem of synthesizing application-specific NoCs Reconfigurable NoC design issues Direction of future research and development in the field of NoC Network-on-Chip: The Next Generation of System-on-Chip Integration covers the basic topics, technology, and future trends relevant to NoC-based design, and can be used by engineers, students, and researchers and other industry professionals interested in computer architecture, embedded systems, and parallel/distributed systems

Toward Reliable, Secure, and Energy-Efficient Multi-Core System Design

Computer hardware researchers have perennially focussed on improving the performance of computers while stipulating the energy consumption under a strict budget. While several innovations over the years have led to high performance and energy efficient computers, more challenges have also emerged as a fallout. For example, smaller transistor devices in modern multi-core systems are afflicted with several reliability and security concerns, which were inconceivable even a decade ago. Tackling these bottlenecks happens to negatively impact the power and performance of the computers. This dissertation explores novel techniques to gracefully solve some of the pressing challenges of the modern computer design. Specifically, the proposed techniques improve the reliability of on-chip communication fabric under a high power supply noise, increase the energy-efficiency of low-power graphics processing units, and demonstrate an unprecedented security loophole of the low-power computing paradigm through rigorous hardware-based experiments

Design Techniques for Energy-Quality Scalable Digital Systems

Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff