656 research outputs found

    Watermarking FPGA Bitfile for Intellectual Property Protection

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    Intellectual property protection (IPP) of hardware designs is the most important requirement for many Field Programmable Gate Array (FPGA) intellectual property (IP) vendors. Digital watermarking has become an innovative technology for IPP in recent years. Existing watermarking techniques have successfully embedded watermark into IP cores. However, many of these techniques share two specific weaknesses: 1) They have extra overhead, and are likely to degrade performance of design; 2) vulnerability to removing attacks. We propose a novel watermarking technique to watermark FPGA bitfile for addressing these weaknesses. Experimental results and analysis show that the proposed technique incurs zero overhead and it is robust against removing attacks

    Hardware Acceleration of Network Intrusion Detection System Using FPGA

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    This thesis presents new algorithms and hardware designs for Signature-based Network Intrusion Detection System (SB-NIDS) optimisation exploiting a hybrid hardwaresoftware co-designed embedded processing platform. The work describe concentrates on optimisation of a complete SB-NIDS Snort application software on a FPGA based hardware-software target rather than on the implementation of a single functional unit for hardware acceleration. Pattern Matching Hardware Accelerator (PMHA) based on Bloom filter was designed to optimise SB-NIDS performance for execution on a Xilinx MicroBlaze soft-core processor. The Bloom filter approach enables the potentially large number of network intrusion attack patterns to be efficiently represented and searched primarily using accesses to FPGA on-chip memory. The thesis demonstrates, the viability of hybrid hardware-software co-designed approach for SB-NIDS. Future work is required to investigate the effects of later generation FPGA technology and multi-core processors in order to clearly prove the benefits over conventional processor platforms for SB-NIDS. The strengths and weaknesses of the hardware accelerators and algorithms are analysed, and experimental results are examined to determine the effectiveness of the implementation. Experimental results confirm that the PMHA is capable of performing network packet analysis for gigabit rate network traffic. Experimental test results indicate that our SB-NIDS prototype implementation on relatively low clock rate embedded processing platform performance is approximately 1.7 times better than Snort executing on a general purpose processor on PC when comparing processor cycles rather than wall clock time

    A Fixed-Latency Architecture to Secure GOOSE and Sampled Value Messages in Substation Systems

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    International Electrotechnical Commission (IEC) 62351-6 standard specifies the security mechanisms to protect real-time communications based on IEC 61850. Generic Object Oriented Substation Events (GOOSE) and Sampled Value (SV) messages must be generated, transmitted and processed in less than 3 ms, which challenges the introduction of IEC 62351-6. After evaluating the security threats to IEC 61850 communications and the state of the art in GOOSE and SV security, this work presents a novel architecture based on wire-speed processing able to provide message authentication and confidentiality. This architecture has been implemented and tested to evaluate its performance, resource usage, and the latency introduced. Other proposals in the scientific literature do not support real-time traffic, so they are not suitable for GOOSE and SV messages. Whereas the others exceed the target latency of 3 ms or do not comply with the standards, our design authenticates and encrypts real-time IEC 61850 data in less than 7 mu s-predictable latency-, and complies with IEC 62351:2020.This work was supported in part by the Ministerio de Economia y Competitividad of Spain under Project TEC2017-84011-R, in part by Fondo Europeo de Desarrollo Regional (FEDER) Funds through the Doctorados Industriales program under Grant DI-15-07857, and in part by the Department of Education, Linguistic Policy and Culture of the Basque Government through the Fund for Research Groups of the Basque University System under Grant IT978-16

    Image Processing Using FPGAs

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    This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs
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