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: 1563935
• 负责人: Timothy Sherwood
• 金额: $ 39.92万
• 依托单位: University of California-Santa Barbara
• 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 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1563935&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。尽管为保护这些信息做了最大的努力，但使用这些数据的计算的副作用，例如计算时间，功耗，电磁辐射，热发射和声学，即使加密也可以用来破译秘密信息。 电力分析攻击特别强大，并且一次又一次地显示出能够从其他安全的设备中快速，可靠地提取最关键的信息，包括智能卡，RFID，微控制器，微处理器，微处理器和其他计算机硬件。从人体中汲取灵感，拟议的研究将开发出新的技术来通过一种计算能力分析的技术分析来开发新技术，以降低技术分析的攻击。一个普通人每分钟眨眼15-20次；实际上，由于眨眼，我们的眼睛闭上了大约10％的清醒时间。随着每一个眨眼，我们大脑的各个部分都会暂时“关闭”，但是我们很少知道这些几乎连续的中断。我们的技术通过动态重新配置设备为设备供电的电网络通过动态重新配置，在计算机系统中在计算机系统中的“连接”和“断开连接”状态的相同复制，看似不可能交错。在计算眨眼期间，处理器的一部分与系统的其余部分暂时断开连接，从而更难修改或检查该计算的副作用（例如功耗）。 我们的创新电路，体系结构，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连接在计算系统中同样不可能。