Reliable Hardware Architectures of CORDIC Algorithm with Fixed Angle of Rotations

Fixed-angle rotation operation of vectors is widely used in signal processing, graphics, and robotics. Various optimized coordinate rotation digital computer (CORDIC) designs have been proposed for uniform rotation of vectors through known and specified angles. Nevertheless, in the presence of faults, such hardware architectures are potentially vulnerable. In this thesis, we propose efficient error detection schemes for two fixed-angle rotation designs, i.e., the Interleaved Scaling and Cascaded Single-rotation CORDIC. To the best of our knowledge, this work is the first in providing reliable architectures for these variants of CORDIC. The former is suitable for low-area applications and, hence, we propose recomputing with encoded operands schemes which add negligible area overhead to the designs. Moreover, the proposed error detection schemes for the latter variant are optimized for efficient applications which hamper the performance of the architectures negligibly. We present three variants of recomputing with encoded operands to detect both transient and permanent faults, coupled with signature-based schemes. The overheads of the proposed designs are assessed through Xilinx FPGA implementations and their effectiveness is benchmarked through error simulations. The results give confidence for the proposed efficient architectures which can be tailored based on the reliability requirements and the overhead to be tolerated

Reliable Hardware Architectures for Cyrtographic Block Ciphers LED and HIGHT

Cryptographic architectures provide different security properties to sensitive usage models. However, unless reliability of architectures is guaranteed, such security properties can be undermined through natural or malicious faults. In this thesis, two underlying block ciphers which can be used in authenticated encryption algorithms are considered, i.e., LED and HIGHT block ciphers. The former is of the Advanced Encryption Standard (AES) type and has been considered areaefficient, while the latter constitutes a Feistel network structure and is suitable for low-complexity and low-power embedded security applications. In this thesis, we propose efficient error detection architectures including variants of recomputing with encoded operands and signature-based schemes to detect both transient and permanent faults. Authenticated encryption is applied in cryptography to provide confidentiality, integrity, and authenticity simultaneously to the message sent in a communication channel. In this thesis, we show that the proposed schemes are applicable to the case study of Simple Lightweight CFB (SILC) for providing authenticated encryption with associated data (AEAD). The error simulations are performed using Xilinx ISE tool and the results are benchmarked for the Xilinx FPGA family Virtex- 7 to assess the reliability capability and efficiency of the proposed architectures

Education and Research Integration of Emerging Multidisciplinary Medical Devices Security

Traditional embedded systems such as secure smart cards and nano-sensor networks have been utilized in various usage models. Nevertheless, emerging secure deeply-embedded systems, e.g., implantable and wearable medical devices, have comparably larger “attack surface”. Specifically, with respect to medical devices, a security breach can be life-threatening (for which adopting traditional solutions might not be practical due to tight constraints of these often-battery-powered systems), and unlike traditional embedded systems, it is not only a matter of financial loss. Unfortunately, although emerging cryptographic engineering research mechanisms for such deeply-embedded systems have started solving this critical, vital problem, university education (at both graduate and undergraduate level) lags comparably. One of the pivotal reasons for such a lag is the multi-disciplinary nature of the emerging security bottlenecks. Based on the aforementioned motivation, in this work, at Rochester Institute of Technology, we present an effective research and education integration strategy to overcome this issue in one of the most critical deeply-embedded systems, i.e., medical devices. Moreover, we present the results of two years of implementation of the presented strategy at graduate-level through fault analysis attacks, a variant of side-channel attacks. We note that the authors also supervise an undergraduate student and the outcome of the presented work has been assessed for that student as well; however, the emphasis is on graduate-level integration. The results of the presented work show the success of the presented methodology while pinpointing the challenges encountered compared to traditional embedded system security research/teaching integration of medical devices security. We would like to emphasize that our integration approaches are general and scalable to other critical infrastructures as well

Lightweight Architectures for Reliable and Fault Detection Simon and Speck Cryptographic Algorithms on FPGA

The widespread use of sensitive and constrained applications necessitates lightweight (lowpower and low-area) algorithms developed for constrained nano-devices. However, nearly all of such algorithms are optimized for platform-based performance and may not be useful for diverse and flexible applications. The National Security Agency (NSA) has proposed two relatively-recent families of lightweight ciphers, i.e., Simon and Speck, designed as efficient ciphers on both hardware and software platforms. This paper proposes concurrent error detection schemes to provide reliable architectures for these two families of lightweight block ciphers. The research work on analyzing the reliability of these algorithms and providing fault diagnosis approaches has not been undertaken to date to the best of our knowledge. The main aim of the proposed reliable architectures is to provide high error coverage while maintaining acceptable area and power consumption overheads. To achieve this, we propose a variant of recomputing with encoded operands. These low-complexity schemes are suited for lowresource applications such as sensitive, constrained implantable and wearable medical devices. We perform fault simulations for the proposed architectures by developing a fault model framework. The architectures are simulated and analyzed on recent field-programmable grate array (FPGA) platforms, and it is shown that the proposed schemes provide high error coverage. The proposed low-complexity concurrent error detection schemes are a step forward towards more reliable architectures for Simon and Speck algorithms in lightweight, secure applications

Multidisciplinary Approaches and Challenges in Integrating Emerging Medical Devices Security Research and Education

Traditional embedded systems such as secure smart cards and nano-sensor networks have been utilized in various usage models. Nevertheless, emerging secure deeply-embedded systems, e.g., implantable and wearable medical devices, have comparably larger “attack surface”. Specifically, with respect to medical devices, a security breach can be life-threatening (for which adopting traditional solutions might not be practical due to tight constraints of these often-battery-powered systems), and unlike traditional embedded systems, it is not only a matter of financial loss. Unfortunately, although emerging cryptographic engineering research mechanisms for such deeply-embedded systems have started solving this critical, vital problem, university education (at both graduate and undergraduate level) lags comparably. One of the pivotal reasons for such a lag is the multi-disciplinary nature of the emerging security bottlenecks. Based on the aforementioned motivation, in this work, at Rochester Institute of Technology, we present an effective research and education integration strategy to overcome this issue in one of the most critical deeply-embedded systems, i.e., medical devices. Moreover, we present the results of two years of implementation of the presented strategy at graduate-level through fault analysis attacks, a variant of side-channel attacks. We note that the authors also supervise an undergraduate student and the outcome of the presented work has been assessed for that student as well; however, the emphasis is on graduate-level integration. The results of the presented work show the success of the presented methodology while pinpointing the challenges encountered compared to traditional embedded system security research/teaching integration of medical devices security. We would like to emphasize that our integration approaches are general and scalable to other critical infrastructures as well

Efficient Error detection Architectures for Low-Energy Block Ciphers with the Case Study of Midori Benchmarked on FPGA

Achieving secure, high performance implementations for constrained applications such as implantable and wearable medical devices is a priority in efficient block ciphers. However, security of these algorithms is not guaranteed in presence of malicious and natural faults. Recently, a new lightweight block cipher, Midori, has been proposed which optimizes the energy consumption besides having low latency and hardware complexity. This algorithm is proposed in two energy-efficient varients, i.e., Midori64 and Midori128, with block sizes equal to 64 and 128 bits. In this thesis, fault diagnosis schemes for variants of Midori are proposed. To the best of the our knowledge, there has been no fault diagnosis scheme presented in the literature for Midori to date. The fault diagnosis schemes are provided for the nonlinear S-box layer and for the round structures with both 64-bit and 128-bit Midori symmetric key ciphers. The proposed schemes are benchmarked on field-programmable gate array (FPGA) and their error coverage is assessed with fault-injection simulations. These proposed error detection architectures make the implementations of this new low-energy lightweight block cipher more reliable

Reliable and Fault-Resilient Schemes for Efficient Radix-4 Complex Division

Complex division is commonly used in various applications in signal processing and control theory including astronomy and nonlinear RF measurements. Nevertheless, unless reliability and assurance are embedded into the architectures of such structures, the suboptimal (and thus erroneous) results could undermine the objectives of such applications. As such, in this thesis, we present schemes to provide complex number division architectures based on (Sweeney, Robertson, and Tocher) SRT-division with fault diagnosis mechanisms. Different fault resilient architectures are proposed in this thesis which can be tailored based on the eventual objectives of the designs in terms of area and time requirements, among which we pinpoint carefully the schemes based on recomputing with shifted operands (RESO) to be able to detect both natural and malicious faults and with proper modification achieve high throughputs. The design also implements a minimized look up table approach which favors in error detection based designs and provides high fault coverage with relatively-low overhead. Additionally, to benchmark the effectiveness of the proposed schemes, extensive fault diagnosis assessments are performed for the proposed designs through fault simulations and FPGA implementations; the design is implemented on Xilinx Spartan-VI and Xilinx Virtex-VI FPGA families

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

Efficient Error Detection Architectures for CORDIC through Recomputing with Encoded Operands

Various optimized coordinate rotation digital computer (CORDIC) designs have been proposed to date. Nonetheless, in the presence of natural faults, such architectures could lead to erroneous outputs. In this paper, we propose error detection schemes for CORDIC architectures used vastly in applications such as complex number multiplication, and singular value decomposition for signal and image processing. To the best of our knowledge, this work is the first in providing reliable architectures for these variants of CORDIC. We present three variants of recomputing with encoded operands to detect both transient and permanent faults. The overheads and effectiveness of the proposed designs are benchmarked through Xilinx FPGA implementations and error simulations. The proposed approaches can be tailored based on overhead tolerance and the reliability constraints to achieve