Reliable and High-Performance Hardware Architectures for the Advanced Encryption Standard/Galois Counter Mode

The high level of security and the fast hardware and software implementations of the Advanced Encryption Standard (AES) have made it the first choice for many critical applications. Since its acceptance as the adopted symmetric-key algorithm, the AES has been utilized in various security-constrained applications, many of which are power and resource constrained and require reliable and efficient hardware implementations. In this thesis, first, we investigate the AES algorithm from the concurrent fault detection point of view. We note that in addition to the efficiency requirements of the AES, it must be reliable against transient and permanent internal faults or malicious faults aiming at revealing the secret key. This reliability analysis and proposing efficient and effective fault detection schemes are essential because fault attacks have become a serious concern in cryptographic applications. Therefore, we propose, design, and implement various novel concurrent fault detection schemes for different AES hardware architectures. These include different structure-dependent and independent approaches for detecting single and multiple stuck-at faults using single and multi-bit signatures. The recently standardized authentication mode of the AES, i.e., Galois/Counter Mode (GCM), is also considered in this thesis. We propose efficient architectures for the AES-GCM algorithm. In this regard, we investigate the AES algorithm and we propose low-complexity and low-power hardware implementations for it, emphasizing on its nonlinear transformation, i.e., SubByes (S-boxes). We present new formulations for this transformation and through exhaustive hardware implementations, we show that the proposed architectures outperform their counterparts in terms of efficiency. Moreover, we present parallel, high-performance new schemes for the hardware implementations of the GCM to improve its throughput and reduce its latency. The performance of the proposed efficient architectures for the AES-GCM and their fault detection approaches are benchmarked using application-specific integrated circuit (ASIC) and field-programmable gate array (FPGA) hardware platforms. Our comparison results show that the proposed hardware architectures outperform their existing counterparts in terms of efficiency and fault detection capability

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

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 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

Методы функционального диагностирования ошибок шифрования в симметричных криптографических системах

Проведено аналіз існуючих рішень з виявлення несправностей та помилок у симетричних криптографічних системах. Розглянуто аналітичну модель поширення помилок. Запропоновано узагальнену методику діагностування помилок шифрування, яка базується на спільних операціях, які використовуються у більшості криптографічних алгоритмів.Known issues analysis of symmetric cryptographic systems fault detection is carried out. Analytic model for error coverage is considered. Generalized procedure for enciphering fault detection based on commonly used operations from most cryptographic algorithms is proposed

A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

Using embedded hardware monitor cores in critical computer systems

The integration of FPGA devices in many different architectures and services makes monitoring and real time detection of errors an important concern in FPGA system design. A monitor is a tool, or a set of tools, that facilitate analytic measurements in observing a given system. The goal of these observations is usually the performance analysis and optimisation, or the surveillance of the system. However, System-on-Chip (SoC) based designs leave few points to attach external tools such as logic analysers. Thus, an embedded error detection core that allows observation of critical system nodes (such as processor cores and buses) should enforce the operation of the FPGA-based system, in order to prevent system failures. The core should not interfere with system performance and must ensure timely detection of errors. This thesis is an investigation onto how a robust hardware-monitoring module can be efficiently integrated in a target PCI board (with FPGA-based application processing features) which is part of a critical computing system. [Continues.

HARDWARE ATTACK DETECTION AND PREVENTION FOR CHIP SECURITY

Hardware security is a serious emerging concern in chip designs and applications. Due to the globalization of the semiconductor design and fabrication process, integrated circuits (ICs, a.k.a. chips) are becoming increasingly vulnerable to passive and active hardware attacks. Passive attacks on chips result in secret information leaking while active attacks cause IC malfunction and catastrophic system failures. This thesis focuses on detection and prevention methods against active attacks, in particular, hardware Trojan (HT). Existing HT detection methods have limited capability to detect small-scale HTs and are further challenged by the increased process variation. We propose to use differential Cascade Voltage Switch Logic (DCVSL) method to detect small HTs and achieve a success rate of 66% to 98%. This work also presents different fault tolerant methods to handle the active attacks on symmetric-key cipher SIMON, which is a recent lightweight cipher. Simulation results show that our Even Parity Code SIMON consumes less area and power than double modular redundancy SIMON and Reversed-SIMON, but yields a higher fault -detection-failure rate as the number of concurrent faults increases. In addition, the emerging technology, memristor, is explored to protect SIMON from passive attacks. Simulation results indicate that the memristor-based SIMON has a unique power characteristic that adds new challenges on secrete key extraction

Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression

The advent of development in three-dimensional (3-D) imaging modalities have generated a massive amount of volumetric data in 3-D images such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US). Existing survey reveals the presence of a huge gap for further research in exploiting reconfigurable computing for 3-D medical image compression. This research proposes an FPGA based co-processing solution to accelerate the mentioned medical imaging system. The HWT block implemented on the sbRIO-9632 FPGA board is Spartan 3 (XC3S2000) chip prototyping board. Analysis and performance evaluation of the 3-D images were been conducted. Furthermore, a novel architecture of context-based adaptive binary arithmetic coder (CABAC) is the advanced entropy coding tool employed by main and higher profiles of H.264/AVC. This research focuses on GPU implementation of CABAC and comparative study of discrete wavelet transform (DWT) and without DWT for 3-D medical image compression systems. Implementation results on MRI and CT images, showing GPU significantly outperforming single-threaded CPU implementation. Overall, CT and MRI modalities with DWT outperform in term of compression ratio, peak signal to noise ratio (PSNR) and latency compared with images without DWT process. For heterogeneous computing, MRI images with various sizes and format, such as JPEG and DICOM was implemented. Evaluation results are shown for each memory iteration, transfer sizes from GPU to CPU consuming more bandwidth or throughput. For size 786, 486 bytes JPEG format, both directions consumed bandwidth tend to balance. Bandwidth is relative to the transfer size, the larger sizing will take more latency and throughput. Next, OpenCL implementation for concurrent task via dedicated FPGA. Finding from implementation reveals, OpenCL on batch procession mode with AOC techniques offers substantial results where the amount of logic, area, register and memory increased proportionally to the number of batch. It is because of the kernel will copy the kernel block refer to batch number. Therefore memory bank increased periodically related to kernel block. It was found through comparative study that the tree balance and unroll loop architecture provides better achievement, in term of local memory, latency and throughput