Quantifiable Assurance: From IPs to Platforms

Hardware vulnerabilities are generally considered more difficult to fix than software ones because they are persistent after fabrication. Thus, it is crucial to assess the security and fix the vulnerabilities at earlier design phases, such as Register Transfer Level (RTL) and gate level. The focus of the existing security assessment techniques is mainly twofold. First, they check the security of Intellectual Property (IP) blocks separately. Second, they aim to assess the security against individual threats considering the threats are orthogonal. We argue that IP-level security assessment is not sufficient. Eventually, the IPs are placed in a platform, such as a system-on-chip (SoC), where each IP is surrounded by other IPs connected through glue logic and shared/private buses. Hence, we must develop a methodology to assess the platform-level security by considering both the IP-level security and the impact of the additional parameters introduced during platform integration. Another important factor to consider is that the threats are not always orthogonal. Improving security against one threat may affect the security against other threats. Hence, to build a secure platform, we must first answer the following questions: What additional parameters are introduced during the platform integration? How do we define and characterize the impact of these parameters on security? How do the mitigation techniques of one threat impact others? This paper aims to answer these important questions and proposes techniques for quantifiable assurance by quantitatively estimating and measuring the security of a platform at the pre-silicon stages. We also touch upon the term security optimization and present the challenges for future research directions

Real Time Automated Counterfeit Integrated Circuit Detection using X-ray Microscopy

Determining the authenticity of integrated circuits is paramount to preventing counterfeit and malicious hardware from being used in critical military, healthcare, aerospace, consumer, and industry applications. Existing techniques to distinguish between authentic and counterfeit integrated circuits (ICs) often include destructive testing requiring subject matter experts. We present a nondestructive technique to detect ICs using x-ray microscopy and advanced imaging analysis with different pattern recognition approaches. Our proposed method is completely automated, and runs in real time. In our approach, images of an integrated circuit are obtained from an x-ray microscope. Local binary pattern features are then extracted from the x-ray image, followed by dimensionality reduction through principal component analysis, and alternatively through a nonlinear principal component methodology using a stacked autoencoder embedded in a deep neural network. From the reduced dimension features, we train two types of learning machines, a support vector machine with a nonlinear kernel and a deep neural network. We present experiments using authentic and ICs to demonstrate that the proposed approach achieves an accuracy of 100% in distinguishing between the counterfeit and authentic samples.This work was supported by the NSF grant NSF/CISE Award #CNS–134427

Inspection of electronic component using pulsed thermography

Counterfeit electronic components (CEC) are of great concern to governments and industry globally as they could lead to systems and mission failure, malfunctioning of safety critical systems, and reduced reliability of high-hazard assets. Depending on the cost of CEC going into the production line, some industries might look to have some sort of inspection capability in-house to screen critical components before they go to assembly. Although advanced counterfeit inspection methods have been developed for a variety of components, they generally exhibit a combination of disadvantages such as destructive, low throughput, high unit cost, or inaccessible to unskilled operator. This paper investigates the potential of pulsed thermography on detection of CEC in a fast and non-destructive manner. The second derivative of post-heat thermal response is used to construct a fingerprint to differentiate genuine and counterfeit components. Results successfully demonstrate the potential of the proposed solution

Nonbanks and risk in retail payments

This paper documents the importance of nonbanks in retail payments in the United States and in 15 European countries and analyzes the implications of the importance and multiple roles played by nonbanks on retail payment risks. This paper also reviews the main regulatory safeguards in place, and concludes that there may be a need to reconsider some of them in view of the growing role of nonbanks and of the global reach of risks in the electronic era.

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

Investigation of Electromagnetic Signatures of a FPGA Using an APREL EM-ISIGHT System

Large military platforms have encountered major performance and reliability issues due to an increased number of incidents with counterfeit electronic parts. This has drawn the attention of Department of Defense (DOD) leadership making detection and avoidance of counterfeit electronic parts a top issue for national defense. More defined regulations and processes for identifying, reporting, and disposing of counterfeit electronic parts are being revised to raise awareness for this aggregating issue, as well as enhance the detection of these parts. Multiple technologies are currently employed throughout the supply chain to detect counterfeit electronic parts. These methods are often costly, time-consuming, and destructive. This research investigates a non-destructive test method that collects unintentionally radiated electromagnetic emissions from functional devices using a commercially available system, the APREL EM-ISight. A design of experiments (DOE) is created and exploited to determine the optimal test settings for measuring devices. The sensitivity of the system is analyzed by scanning a commercial-off-the-shelf (COTS) field-programmable gate array (FPGA) at the optimal test settings established from the DOE and varying the programmed signal. This research established the viability of using APRELs EM-ISight to detect a devices inherent electromagnetic signature. Another take away from this research is the tradeoff between resolution and scantime

Sustainable Fault-handling Of Reconfigurable Logic Using Throughput-driven Assessment

A sustainable Evolvable Hardware (EH) system is developed for SRAM-based reconfigurable Field Programmable Gate Arrays (FPGAs) using outlier detection and group testing-based assessment principles. The fault diagnosis methods presented herein leverage throughput-driven, relative fitness assessment to maintain resource viability autonomously. Group testing-based techniques are developed for adaptive input-driven fault isolation in FPGAs, without the need for exhaustive testing or coding-based evaluation. The techniques maintain the device operational, and when possible generate validated outputs throughout the repair process. Adaptive fault isolation methods based on discrepancy-enabled pair-wise comparisons are developed. By observing the discrepancy characteristics of multiple Concurrent Error Detection (CED) configurations, a method for robust detection of faults is developed based on pairwise parallel evaluation using Discrepancy Mirror logic. The results from the analytical FPGA model are demonstrated via a self-healing, self-organizing evolvable hardware system. Reconfigurability of the SRAM-based FPGA is leveraged to identify logic resource faults which are successively excluded by group testing using alternate device configurations. This simplifies the system architect\u27s role to definition of functionality using a high-level Hardware Description Language (HDL) and system-level performance versus availability operating point. System availability, throughput, and mean time to isolate faults are monitored and maintained using an Observer-Controller model. Results are demonstrated using a Data Encryption Standard (DES) core that occupies approximately 305 FPGA slices on a Xilinx Virtex-II Pro FPGA. With a single simulated stuck-at-fault, the system identifies a completely validated replacement configuration within three to five positive tests. The approach demonstrates a readily-implemented yet robust organic hardware application framework featuring a high degree of autonomous self-control

Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets

The density, porosity, breaking force, viscoelastic properties, and the presence or absence of any structural defects or irregularities are important physical-mechanical quality attributes of popular solid dosage forms like tablets. The irregularities associated with these attributes may influence the drug product functionality. Thus, an accurate and efficient characterization of these properties is critical for successful development and manufacturing of a robust tablets. These properties are mainly analyzed and monitored with traditional pharmacopeial and non-pharmacopeial methods. Such methods are associated with several challenges such as lack of spatial resolution, efficiency, or sample-sparing attributes. Recent advances in technology, design, instrumentation, and software have led to the emergence of newer techniques for non-invasive characterization of physical-mechanical properties of tablets. These techniques include near infrared spectroscopy, Raman spectroscopy, X-ray microtomography, nuclear magnetic resonance (NMR) imaging, terahertz pulsed imaging, laser-induced breakdown spectroscopy, and various acoustic- and thermal-based techniques. Such state-of-the-art techniques are currently applied at various stages of development and manufacturing of tablets at industrial scale. Each technique has specific advantages or challenges with respect to operational efficiency and cost, compared to traditional analytical methods. Currently, most of these techniques are used as secondary analytical tools to support the traditional methods in characterizing or monitoring tablet quality attributes. Therefore, further development in the instrumentation and software, and studies on the applications are necessary for their adoption in routine analysis and monitoring of tablet physical-mechanical properties

Construction industry 4.0 and sustainability: an enabling framework

Governments worldwide are taking actions to address the construction sector's sustainability concerns, including high carbon emissions, health and safety risks, low productivity, and increasing costs. Applying Industry 4.0 technologies to construction (also referred to as Construction 4.0) could address some of these concerns. However, current understanding about this is quite limited, with previous work being largely fragmented and limited both in terms of technologies as well as their interrelationships with the triple bottom line of sustainability perspectives. The focus of this article is therefore on addressing these gaps by proposing a comprehensive multi-dimensional Construction 4.0 sustainability framework that identifies and categorizes the key Construction 4.0 technologies and their positive and negative impacts on environmental, economic, and social sustainability, and then establishing its applicability/usefulness through an empirical, multimethodology case study assessment of the UAE's construction sector. The findings indicate Construction 4.0’s positive impacts on environmental and economic sustainability that far outweigh its negative effects, although these impacts are comparable with regards to social sustainability. On Construction 4.0 technologies itself, their application was found to be nonuniform with greater application seen for building information modeling and automation vis-à-vis others such as cyber-physical systems and smart materials, with significant growth expected in the future for blockchain- and three-dimensional-printing-related technologies. The proposed novel framework could enable the development of policy interventions and support mechanisms to increase Construction 4.0 deployment while addressing its negative sustainability-related impacts. The framework also has the potential to be adapted and applied to other country and sectoral contexts

Novel approaches to the detection of substandard medicines

This thesis addresses the serious implications of substandard medicines to public health care and describes attempts to bridge the apparent gap of detecting substandard medicines by exploring new detection approaches in pharmacovigilance and in analytical technologies as well as validating these methods in a field study. Substandard medicines (SSMs) are licensed medicines, that most commonly contain either too little or too much active pharmaceutical ingredient (API). SSMs may be the result of negligence, error and/or low standard of quality control of the manufacturing process (non-good manufacturing accredited status) and/or distribution process (degradation of medicinal products through bad storage). The use of SSMs may result in severe adverse events (AEs) and even death and may promote antimicrobial resistance. Evidence of high increases of SSMs, predominantly in developing countries, reveals that there is a need for easy, rapid and affordable detection tools. Currently, there is no portable screening device in the market that can accurately measure the content of API of medicinal samples. The only available device, currently under development, is PharmaChk, an innovative analytical instrument, that is able to quantify the amount of a number of APIs (e.g. artemisinin, tetracycline) and evaluate their dissolution profile. In collaboration with the Biomechanical Department of Boston University, we conducted further research on this device. The assay for essential antimalarial drug Coartem® (artemether and lumefantrine) was developed and used for a field study in Zimbabwe. In addition to analytical detection, pharmacovigilance signal detection techniques have been shown to be effective in detecting SSMs. Preliminary research (conducted by the WHO Uppsala Monitoring Centre) exists on using data mining algorithms on the WHO Vigibase® data set of global individual case safety reports to identify SSMs. After validation of this pharmacovigilance screening tool and the assay of Coartem® on the PharmaChk device and in order to assess the efficiency of these two detection approaches of SSMs in real world practice, we initiated a field study on Coartem® and its generic versions in Zimbabwe. Malaria is a major health burden in this country with 8,000,000 people at risk (50% of the population). Previous studies have shown that Zimbabweans are at high risk from substandard and falsified medicines, resulting in increased mortality, morbidity, financial strain and long-term antimicrobial resistance. We collected samples from sites of the private health sector as well as from sites that were conveniently accessible. The purchase of samples was performed in 18 cities in areas with high risk for malaria. The quality of purchased samples was tested through qualitative and quantitative measurements using different screening field devices including Raman, Near-Infrared spectrometry and X-Ray Fluorescence as well as spectrophotometer and high performance liquid chromatography (HPLC) analysis for confirmatory analysis in analytical laboratories in Zimbabwe, Switzerland and the United States. Data mining for the antimalarial drug Coartem® identified no excess reporting of AEs in Zimbabwe. Analyses of all screening and confirmatory analytical technologies revealed a good quality of all collected samples. The PharmaChk device demonstrated comparable results of the collected samples to HPLC, which is the gold standard method. The analytical screening tool PharmaChk was able to determine that there was no unexpected risk with essential medicine artemether/lumefantrine in Zimbabwe. This pilot study highlighted the potential of these two detection methods (pharmacovigilance screening tool and analytical detection tool using the PharmaChk device). However, further research on a larger scale of samples and other therapeutic areas is required to validate these findings. This thesis highlights the need and importance of collaborations in identifying SSMs. Without the partnership between academia, industry and private laboratory institutions this research may have not been possible. The complex issue of SSMs requires this kind of engagement to enhance safe and effective medical treatment by decreasing the number of circulating SSMs worldwide