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Hardware Security for Approximate Computing

近似计算的硬件安全

基本信息

批准号：
EP/X009602/1
负责人：
CHONGYAN GU
金额：
$ 37.98万
依托单位：
Queen's University Belfast
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2023
资助国家：
英国
起止时间：
2023 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FX009602%2F1
关键词：
Hardware Security Approximate Computing

项目摘要

As IBM's 2nm chip is pushing Moore's law approaching its limit, conventional computing techniques are struggling to offer high performance computing within power consumption constraints. Inspired by the fault tolerance capability of the human brain, approximate computing, which is error tolerant, can offer a huge reduction in computer power consumption without affecting the results (such as accuracy) of certain human perception and recognition related computation that only require a result to be approximate, rather than accurate. Examples include Artificial Intelligence (AI), Deep Learning (DL), image processing and even some cryptographic schemes. However, approximate computing has been shown to have security vulnerabilities due to the unpredictability of intrinsic errors that may be indistinguishable from malicious modifications. Due to the inherent power and area savings achieved by approximate computing, security countermeasures shold also be lightweight ande efficient. Hence, the aim of this proposal is to use advanced hardware security techniques to enable the development of approximate computing technologies that have both optimal security protection and optimal system efficiency. Currently, no comprehensive research has been conducted to date into security of approximate computing or into countermeasures that protect such designs.Physical unclonable function (PUF), as a lightweight hardware security primitive, is one of the best candidates for securing resource-constrained applications, such as approximate computing. A PUF can be used to generate a unique digital fingerprint for an electronic device based on manufacturing process variations of silicon chips. Currently, PUFs have been widely studied for conventional computing but no effective intrinsic PUF designs using approximate techniques have been presented. This project is timely because approximate computing has rapidly attracted attention from both academica and industry, as it addresses one of the fundamental barriers in computing systems, power dissipation, but it has also opened new vectors of attacks. This project will develop an intrinsic PUF design based on the normal operations of an approximate processor without the need for addtional hardware resource. The project will aslo address for the first time how to achieve secure and effective approximate computing designs.Thales UK, a leader in designing and building mission-critical information systems for the defence, security, aerospace, and transportation sections, has already invited the PI to join the Thales CyRes-Advance project to investigate security protection for connected and autonomous vechicles (CAVs) by considering hardware security. Thales will provide £250k in-kind support, such as technical advice/review of the hardware design, access to Thales CAV test platform and experimental validation for the project, to accelerate the research process and produce high-quality research outputs.

由于IBM的2纳米芯片正在推动摩尔定律接近极限，传统计算技术正在努力在功耗限制内提供高性能计算。受人脑的容错能力的启发，容错的近似计算可以提供计算机功耗的巨大降低，而不影响某些人类感知和识别相关计算的结果（例如准确性），这些计算仅需要结果是近似的而不是准确的。例子包括人工智能（AI），深度学习（DL），图像处理，甚至一些加密方案。然而，近似计算已被证明具有安全漏洞，由于内在错误的不可预测性，可能无法区分恶意修改。由于通过近似计算实现的固有功率和面积节省，安全对策也应该是轻量级的和高效的。因此，本提案的目的是使用先进的硬件安全技术，以实现具有最佳安全保护和最佳系统效率的近似计算技术的开发。物理不可克隆函数（PUF）作为一种轻量级的硬件安全原语，是保证近似计算等资源受限应用安全的最佳选择之一。PUF可以用于基于硅芯片的制造工艺变化来生成电子设备的唯一数字指纹。目前，PUF已被广泛研究用于常规计算，但没有提出使用近似技术的有效的本征PUF设计。这个项目是及时的，因为近似计算已经迅速引起了学术界和工业界的关注，因为它解决了计算系统中的一个基本障碍，即功耗，但它也开辟了新的攻击途径。本计画将开发一个基于近似处理器正常运作的内建式PUF设计，而不需要额外的硬体资源。该项目还将首次解决如何实现安全有效的近似计算设计问题。英国泰雷兹公司是为国防、安全、航空航天和运输部门设计和构建关键任务信息系统的领导者，已经邀请PI加入泰雷兹CyRes-Advance项目，研究从硬件安全角度出发，为互联和自主车辆（CAV）提供安全保护。泰雷兹将提供25万英镑的实物支持，如硬件设计的技术咨询/审查，使用泰雷兹CAV测试平台和对该项目进行实验验证，以加快研究进程并产生高质量的研究成果。