STARSS: Small: Side-Channel Analysis and Resiliency Targeting Accelerators

STARSS：小型：侧通道分析和弹性目标加速器

• 批准号: 1618379
• 负责人: David Kaeli
• 金额: $ 30万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618379&HistoricalAwards=false
• 关键词: STARSS; Small; Side; Channel; Analysis

Today's computing systems are becoming increasingly heterogeneous, providing new levels of computational horsepower and power efficiency. Hardware accelerators are a key element in this trend, allowing compute-oriented code to be offloaded to specialized hardware. Accelerators are starting to be used for security services, where high-volume data is encrypted to ensure integrity/confidentiality. However, the security of accelerators has only just begun to receive attention. Issues such as information leakage through side channels have not been addressed. Secure data will continue to grow in importance as we enter into the era of the Internet-of-Things (IoT). This project addresses national security needs, helping individuals, companies and governments to protect their data.This project develops new knowledge of the attack surface of accelerator devices that are becoming attractive platforms for encryption acceleration. A new class of resiliency approaches are developed to guard sensitive data and reduce the attack surface. The project evaluates side-channel attack vulnerability on a range of systems, including discrete GPUs, integrated APUs (devices with the CPU and GPU sharing memory), and other classes of accelerators. The 3 classes of attacks include: 1) timing attacks, 2) power analysis attacks and 3) electromagnetic emanation attacks. Three resiliency mechanisms are studied: 1) software obfuscation, 2) compiler-assisted modifications to address power/EM leakage, and 3) hardware techniques that add significant timing noise. The project develops tutorials on reliability issues present in accelerator devices. The project provides multiple opportunities for undergraduates from under-represented groups to engage in security-related research.

今天的计算系统正变得越来越异构化，提供了更高水平的计算能力和能效。硬件加速器是这一趋势的关键因素，它允许面向计算的代码被卸载到专门的硬件上。加速器开始用于安全服务，对大量数据进行加密以确保完整性/机密性。然而，加速器的安全性才刚刚开始受到关注。通过旁路泄露信息等问题尚未得到解决。随着我们进入物联网(IoT)时代，安全数据的重要性将继续增长。该项目解决了国家安全需求，帮助个人、公司和政府保护他们的数据。该项目开发了有关加速器设备攻击面的新知识，这些设备正在成为具有吸引力的加密加速平台。开发了一类新的弹性方法来保护敏感数据并减少攻击面。该项目评估了一系列系统上的侧通道攻击漏洞，包括离散GPU、集成APU(CPU和GPU共享内存的设备)和其他类别的加速器。这3类攻击包括：1)定时攻击，2)功率分析攻击和3)电磁辐射攻击。研究了三种弹性机制：1)软件混淆，2)编译器辅助修改以解决功率/EM泄漏，以及3)显著增加时序噪声的硬件技术。该项目开发关于加速器设备中存在的可靠性问题的教程。该项目为来自代表性不足群体的本科生提供了多种从事与安全有关的研究的机会。