1,273 research outputs found

    SCM : Secure Code Memory Architecture

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    An increasing number of applications implemented on a SoC (System-on-chip) require security features. This work addresses the issue of protecting the integrity of code and read-only data that is stored in memory. To this end, we propose a new architecture called SCM, which works as a standalone IP core in a SoC. To the best of our knowledge, there exist no architectural elements similar to SCM that offer the same strict security guarantees while, at the same time, not requiring any modifications to other IP cores in its SoC design. In addition, SCM has the flexibility to select the parts of the software to be protected, which eases the integration of our solution with existing software. The evaluation of SCM was done on the Zynq platform which features an ARM processor and an FPGA. The design was evaluated by executing a number of different benchmarks from memory protected by SCM, and we found that it introduces minimal overhead to the system

    SECURE AND LIGHTWEIGHT HARDWARE AUTHENTICATION USING ISOLATED PHYSICAL UNCLONABLE FUNCTION

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    As embedded computers become ubiquitous, mobile and more integrated in connectivity, user dependence on integrated circuits (ICs) increases massively for handling security sensitive tasks as well as processing sensitive information. During this process, hardware authentication is important to prevent unauthorized users or devices from gaining access to secret information. An effective method for hardware authentication is by using physical unclonable function (PUF), which is a hardware design that leverages intrinsic unique physical characteristics of an IC, such as propagation delay, for security authentication in real time. However, PUF is vulnerable to modeling attacks, as one can design an algorithm to imitate PUF functionality at the software level given a sufficient set of challenge-response pairs (CRPs). To address the problem, we employ hardware isolation primitives (e.g., ARM TrustZone) to protect PUF. The key idea is to physically isolate the system resources that handle security-sensitive information from the regular ones. This technique can be implemented by isolating and strictly controlling any connection between the secure and normal resources. We design and implement a ring oscillator (RO)-based PUF with hardware isolation protection using ARM TrustZone. Our PUF design heavily limits the number of CRPs a potential attacker has access to. Therefore, the modeling attack cannot be performed accurately enough to guess the response of the PUF to a challenge. Furthermore, we develop and demonstrate a brand new application for the designed PUF, namely multimedia authentication, which is an integral part of multimedia signal processing in many real-time and security sensitive applications. We show that the PUF-based hardware security approach is capable of accomplishing the authentication for both the hardware device and the multimedia stream while introducing minimum overhead. Finally, we evaluate the hardware-isolated PUF design using a prototype implementation on a Xilinx system on chip (SoC). Particularly, we conduct functional evaluation (i.e., randomness, uniqueness, and correctness), security analysis against modeling attacks, as well as performance and overhead evaluation (i.e., response time and resource usages). Our experimental results on the real hardware demonstrate the high security and low overhead of the PUF in real time authentication. Advisor: Sheng We

    A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

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    This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast 128x64128\mathrm{x}64 binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode (10μW10\mu W at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between 193μW193\mu W and 277μW277\mu W, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa
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