2,129 research outputs found

    Efficient Implementation on Low-Cost SoC-FPGAs of TLSv1.2 Protocol with ECC_AES Support for Secure IoT Coordinators

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    Security management for IoT applications is a critical research field, especially when taking into account the performance variation over the very different IoT devices. In this paper, we present high-performance client/server coordinators on low-cost SoC-FPGA devices for secure IoT data collection. Security is ensured by using the Transport Layer Security (TLS) protocol based on the TLS_ECDHE_ECDSA_WITH_AES_128_CBC_SHA256 cipher suite. The hardware architecture of the proposed coordinators is based on SW/HW co-design, implementing within the hardware accelerator core Elliptic Curve Scalar Multiplication (ECSM), which is the core operation of Elliptic Curve Cryptosystems (ECC). Meanwhile, the control of the overall TLS scheme is performed in software by an ARM Cortex-A9 microprocessor. In fact, the implementation of the ECC accelerator core around an ARM microprocessor allows not only the improvement of ECSM execution but also the performance enhancement of the overall cryptosystem. The integration of the ARM processor enables to exploit the possibility of embedded Linux features for high system flexibility. As a result, the proposed ECC accelerator requires limited area, with only 3395 LUTs on the Zynq device used to perform high-speed, 233-bit ECSMs in 413 µs, with a 50 MHz clock. Moreover, the generation of a 384-bit TLS handshake secret key between client and server coordinators requires 67.5 ms on a low cost Zynq 7Z007S device

    Multi-Tenant Cloud FPGA: A Survey on Security

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    With the exponentially increasing demand for performance and scalability in cloud applications and systems, data center architectures evolved to integrate heterogeneous computing fabrics that leverage CPUs, GPUs, and FPGAs. FPGAs differ from traditional processing platforms such as CPUs and GPUs in that they are reconfigurable at run-time, providing increased and customized performance, flexibility, and acceleration. FPGAs can perform large-scale search optimization, acceleration, and signal processing tasks compared with power, latency, and processing speed. Many public cloud provider giants, including Amazon, Huawei, Microsoft, Alibaba, etc., have already started integrating FPGA-based cloud acceleration services. While FPGAs in cloud applications enable customized acceleration with low power consumption, it also incurs new security challenges that still need to be reviewed. Allowing cloud users to reconfigure the hardware design after deployment could open the backdoors for malicious attackers, potentially putting the cloud platform at risk. Considering security risks, public cloud providers still don't offer multi-tenant FPGA services. This paper analyzes the security concerns of multi-tenant cloud FPGAs, gives a thorough description of the security problems associated with them, and discusses upcoming future challenges in this field of study

    Hardware Architectures for Post-Quantum Cryptography

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    The rapid development of quantum computers poses severe threats to many commonly-used cryptographic algorithms that are embedded in different hardware devices to ensure the security and privacy of data and communication. Seeking for new solutions that are potentially resistant against attacks from quantum computers, a new research field called Post-Quantum Cryptography (PQC) has emerged, that is, cryptosystems deployed in classical computers conjectured to be secure against attacks utilizing large-scale quantum computers. In order to secure data during storage or communication, and many other applications in the future, this dissertation focuses on the design, implementation, and evaluation of efficient PQC schemes in hardware. Four PQC algorithms, each from a different family, are studied in this dissertation. The first hardware architecture presented in this dissertation is focused on the code-based scheme Classic McEliece. The research presented in this dissertation is the first that builds the hardware architecture for the Classic McEliece cryptosystem. This research successfully demonstrated that complex code-based PQC algorithm can be run efficiently on hardware. Furthermore, this dissertation shows that implementation of this scheme on hardware can be easily tuned to different configurations by implementing support for flexible choices of security parameters as well as configurable hardware performance parameters. The successful prototype of the Classic McEliece scheme on hardware increased confidence in this scheme, and helped Classic McEliece to get recognized as one of seven finalists in the third round of the NIST PQC standardization process. While Classic McEliece serves as a ready-to-use candidate for many high-end applications, PQC solutions are also needed for low-end embedded devices. Embedded devices play an important role in our daily life. Despite their typically constrained resources, these devices require strong security measures to protect them against cyber attacks. Towards securing this type of devices, the second research presented in this dissertation focuses on the hash-based digital signature scheme XMSS. This research is the first that explores and presents practical hardware based XMSS solution for low-end embedded devices. In the design of XMSS hardware, a heterogenous software-hardware co-design approach was adopted, which combined the flexibility of the soft core with the acceleration from the hard core. The practicability and efficiency of the XMSS software-hardware co-design is further demonstrated by providing a hardware prototype on an open-source RISC-V based System-on-a-Chip (SoC) platform. The third research direction covered in this dissertation focuses on lattice-based cryptography, which represents one of the most promising and popular alternatives to today\u27s widely adopted public key solutions. Prior research has presented hardware designs targeting the computing blocks that are necessary for the implementation of lattice-based systems. However, a recurrent issue in most existing designs is that these hardware designs are not fully scalable or parameterized, hence limited to specific cryptographic primitives and security parameter sets. The research presented in this dissertation is the first that develops hardware accelerators that are designed to be fully parameterized to support different lattice-based schemes and parameters. Further, these accelerators are utilized to realize the first software-harware co-design of provably-secure instances of qTESLA, which is a lattice-based digital signature scheme. This dissertation demonstrates that even demanding, provably-secure schemes can be realized efficiently with proper use of software-hardware co-design. The final research presented in this dissertation is focused on the isogeny-based scheme SIKE, which recently made it to the final round of the PQC standardization process. This research shows that hardware accelerators can be designed to offload compute-intensive elliptic curve and isogeny computations to hardware in a versatile fashion. These hardware accelerators are designed to be fully parameterized to support different security parameter sets of SIKE as well as flexible hardware configurations targeting different user applications. This research is the first that presents versatile hardware accelerators for SIKE that can be mapped efficiently to both FPGA and ASIC platforms. Based on these accelerators, an efficient software-hardwareco-design is constructed for speeding up SIKE. In the end, this dissertation demonstrates that, despite being embedded with expensive arithmetic, the isogeny-based SIKE scheme can be run efficiently by exploiting specialized hardware. These four research directions combined demonstrate the practicability of building efficient hardware architectures for complex PQC algorithms. The exploration of efficient PQC solutions for different hardware platforms will eventually help migrate high-end servers and low-end embedded devices towards the post-quantum era

    Virtualized Reconfigurable Resources and Their Secured Provision in an Untrusted Cloud Environment

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    The cloud computing business grows year after year. To keep up with increasing demand and to offer more services, data center providers are always searching for novel architectures. One of them are FPGAs, reconfigurable hardware with high compute power and energy efficiency. But some clients cannot make use of the remote processing capabilities. Not every involved party is trustworthy and the complex management software has potential security flaws. Hence, clients’ sensitive data or algorithms cannot be sufficiently protected. In this thesis state-of-the-art hardware, cloud and security concepts are analyzed and com- bined. On one side are reconfigurable virtual FPGAs. They are a flexible resource and fulfill the cloud characteristics at the price of security. But on the other side is a strong requirement for said security. To provide it, an immutable controller is embedded enabling a direct, confidential and secure transfer of clients’ configurations. This establishes a trustworthy compute space inside an untrusted cloud environment. Clients can securely transfer their sensitive data and algorithms without involving vulnerable software or a data center provider. This concept is implemented as a prototype. Based on it, necessary changes to current FPGAs are analyzed. To fully enable reconfigurable yet secure hardware in the cloud, a new hybrid architecture is required.Das Geschäft mit dem Cloud Computing wächst Jahr für Jahr. Um mit der steigenden Nachfrage mitzuhalten und neue Angebote zu bieten, sind Betreiber von Rechenzentren immer auf der Suche nach neuen Architekturen. Eine davon sind FPGAs, rekonfigurierbare Hardware mit hoher Rechenleistung und Energieeffizienz. Aber manche Kunden können die ausgelagerten Rechenkapazitäten nicht nutzen. Nicht alle Beteiligten sind vertrauenswürdig und die komplexe Verwaltungssoftware ist anfällig für Sicherheitslücken. Daher können die sensiblen Daten dieser Kunden nicht ausreichend geschützt werden. In dieser Arbeit werden modernste Hardware, Cloud und Sicherheitskonzept analysiert und kombiniert. Auf der einen Seite sind virtuelle FPGAs. Sie sind eine flexible Ressource und haben Cloud Charakteristiken zum Preis der Sicherheit. Aber auf der anderen Seite steht ein hohes Sicherheitsbedürfnis. Um dieses zu bieten ist ein unveränderlicher Controller eingebettet und ermöglicht eine direkte, vertrauliche und sichere Übertragung der Konfigurationen der Kunden. Das etabliert eine vertrauenswürdige Rechenumgebung in einer nicht vertrauenswürdigen Cloud Umgebung. Kunden können sicher ihre sensiblen Daten und Algorithmen übertragen ohne verwundbare Software zu nutzen oder den Betreiber des Rechenzentrums einzubeziehen. Dieses Konzept ist als Prototyp implementiert. Darauf basierend werden nötige Änderungen von modernen FPGAs analysiert. Um in vollem Umfang eine rekonfigurierbare aber dennoch sichere Hardware in der Cloud zu ermöglichen, wird eine neue hybride Architektur benötigt

    GuardNN: Secure DNN Accelerator for Privacy-Preserving Deep Learning

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    This paper proposes GuardNN, a secure deep neural network (DNN) accelerator, which provides strong hardware-based protection for user data and model parameters even in an untrusted environment. GuardNN shows that the architecture and protection can be customized for a specific application to provide strong confidentiality and integrity protection with negligible overhead. The design of the GuardNN instruction set reduces the TCB to just the accelerator and enables confidentiality protection without the overhead of integrity protection. GuardNN also introduces a new application-specific memory protection scheme to minimize the overhead of memory encryption and integrity verification. The scheme shows that most of the off-chip meta-data in today's state-of-the-art memory protection can be removed by exploiting the known memory access patterns of a DNN accelerator. GuardNN is implemented as an FPGA prototype, which demonstrates effective protection with less than 2% performance overhead for inference over a variety of modern DNN models

    Toward Fault-Tolerant Applications on Reconfigurable Systems-on-Chip

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    L'abstract è presente nell'allegato / the abstract is in the attachmen
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