TWC: Medium: Collaborative: Computational Blinking - Computer Architecture Techniques for Mitigating Side Channels

TWC：媒介：协作：计算闪烁 - 用于缓解侧通道的计算机体系结构技术

• 批准号: 1563767
• 负责人: Ryan Kastner
• 金额: $ 81.6万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1563767&HistoricalAwards=false
• 关键词: TWC; Medium; Collaborative; Computational; Blinking

Computer systems increasingly perform operations on critical and confidential data. Despite best efforts to protect this information, the side effects of computations using this data, e.g., the computation time, the power consumption, electromagnetic radiation, thermal emanations, and acoustics, can be used to decipher secret information even when it is encrypted. Power analysis attacks are particularly powerful and have been shown time and again to be able to quickly and reliably extract the most critical information from otherwise secure devices including smart cards, RFIDs, microcontrollers, microprocessors, and other computing hardware.Drawing inspiration from the human body, the proposed research will develop new techniques to mitigate power analysis attacks through a technique called computational blinking. An average person blinks 15-20 times per minute; in fact our eyes are closed around 10% of our waking hours due to blinking. With each and every blink, sections of our brain are momentarily "powered off," yet we are rarely even aware of these near continuous interruptions. Our techniques replicate this same, seemingly imperceivable interleaving of "connected" and "disconnected" states in a computer system through the dynamic reconfiguration of the electrical network powering a device. During a computational blink, a portion of the processor is momentarily electrically disconnected from the rest of the system making it more difficult to modify or examine the side effects (e.g., power consumption) of that computation. Our innovative circuits, architectures, run-time systems, programming frameworks, design tools, and measurement methodologies make these intermittent disconnections just as imperceivable in computing systems.

计算机系统越来越多地对关键和机密数据执行操作。尽管尽了最大努力来保护这些信息，但使用这些数据进行计算的副作用，例如，计算时间、功率消耗、电磁辐射、热辐射和声学可以用于解密秘密信息，即使当其被加密时。 功耗分析攻击特别强大，已经多次被证明能够快速可靠地从智能卡、RFID、微控制器、微处理器和其他计算硬件等安全设备中提取最关键的信息。从人体中汲取灵感，拟议的研究将开发新技术，通过一种称为计算闪烁的技术来减轻功耗分析攻击。一个人平均每分钟眨眼15-20次;事实上，由于眨眼，我们的眼睛大约有10%的清醒时间是闭着的。每一次眨眼，我们大脑的某些部分都会暂时“断电”，但我们很少意识到这些近乎连续的中断。我们的技术通过动态重新配置为设备供电的电网，在计算机系统中复制了这种相同的、看似不可感知的“连接”和“断开”状态的交织。在计算闪烁期间，处理器的一部分暂时与系统的其余部分电断开，使得更难以修改或检查副作用（例如，功耗）的计算。 我们的创新电路、架构、运行时系统、编程框架、设计工具和测量方法使这些间歇性断开在计算系统中变得不可感知。