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CRII: SaTC: Investigation of Side-Channel Attack Vulnerability in Near-Threshold Computing Systems

CRII：SaTC：近阈值计算系统中的侧通道攻击漏洞调查

基本信息

批准号：
1657562
负责人：
Xuan Zhang
金额：
$ 17.5万
依托单位：
Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-05-01 至 2020-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1657562&HistoricalAwards=false
关键词：
CRII SaTC Investigation Side Channel

项目摘要

Security breaches in computing systems cost billions of dollars in economic damages every year, and the intangible destructive consequences left by malicious attacks are inestimable. Meanwhile, near-threshold computing (NTC) emerges as a promising solution to improve energy efficiency by reducing the supply voltage, making it attractive for a broad range of applications from Internet-of-Things (IoT) devices to cloud computing facilities. With the anticipated adoption of NTC in mainstream computing systems, security vulnerabilities that are unique to NTC will be ripe for exploitation. The objective of this project is to, for the first time, address NTC security concerns by performing a thorough and systematic investigation of its unique vulnerabilities to Side-Channel Attack (SCA) - attacks that rely on information leaked from the physical implementation of a cryptosystem.Side-channel attacks are perhaps one of the most covert and sophisticated among cyber threats. Instead of treating security as an after-thought in traditional hardware development, in this project, we explore early-stage preventative methods to identify secure concerns in the design phase across different hardware implementation layers, and investigate the fundamental trade-off between efficiency and security in computing systems. Our investigation of the security implications of NTC will provide critical insights and methodologies for designing future efficient and secure computing systems. Due to its multi-disciplinary nature, our research project will promote the development and training of a strong workforce well-versed in the critical security domain across circuit design, computer architecture, and cryptography.

计算系统中的安全漏洞每年造成数十亿美元的经济损失，恶意攻击留下的无形破坏性后果无法估量。与此同时，近阈值计算（NTC）作为一种有前途的解决方案，通过降低电源电压来提高能源效率，使其对从物联网（IoT）设备到云计算设施的广泛应用具有吸引力。随着NTC在主流计算系统中的预期采用，NTC特有的安全漏洞将成熟，可以利用。该项目的目标是，通过对NTC遭受侧信道攻击（SCA）的独特漏洞进行彻底和系统的调查，首次解决NTC的安全问题。侧信道攻击是一种依赖于加密系统物理实现中泄露的信息的攻击。侧信道攻击可能是网络威胁中最隐蔽和最复杂的攻击之一。在这个项目中，我们没有将安全性视为传统硬件开发中的事后考虑，而是探索早期预防方法，以在不同硬件实现层的设计阶段识别安全问题，并调查计算系统中效率和安全性之间的基本权衡。我们对NTC的安全影响的调查将为设计未来高效和安全的计算系统提供重要的见解和方法。由于其多学科性质，我们的研究项目将促进发展和培训一支精通电路设计，计算机体系结构和密码学的关键安全领域的强大劳动力。

项目成果

期刊论文数量（11）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices

DOI：
10.1109/iccad45719.2019.8942099
发表时间：
2019-11
期刊：
2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
影响因子：
0
作者：
Weidong Cao;Liu Ke;Ayan Chakrabarti;Xuan Zhang
通讯作者：
Weidong Cao;Liu Ke;Ayan Chakrabarti;Xuan Zhang

AxTrain: Hardware-Oriented Neural Network Training for Approximate Inference

DOI：
10.1145/3218603.3218643
发表时间：
2018-05
期刊：
Proceedings of the International Symposium on Low Power Electronics and Design
影响因子：
0
作者：
Xin He;Liu Ke;Wenyan Lu;Guihai Yan;Xuan Zhang
通讯作者：
Xin He;Liu Ke;Wenyan Lu;Guihai Yan;Xuan Zhang

NeuADC: Neural Network-Inspired RRAM-Based Synthesizable Analog-to-Digital Conversion with Reconfigurable Quantization Support

DOI：
10.23919/date.2019.8714933
发表时间：
2019-03
期刊：
2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)
影响因子：
0
作者：
Weidong Cao;Xin He;Ayan Chakrabarti;Xuan Zhang
通讯作者：
Weidong Cao;Xin He;Ayan Chakrabarti;Xuan Zhang

Evaluating Neural Network-Inspired Analog-to-Digital Conversion With Low-Precision RRAM

DOI：
10.1109/tcad.2020.3013563
发表时间：
2021-05
期刊：
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
影响因子：
2.9
作者：
Weidong Cao;Liu Ke;Ayan Chakrabarti;Xuan Zhang
通讯作者：
Weidong Cao;Liu Ke;Ayan Chakrabarti;Xuan Zhang

Exploiting Read/Write Asymmetry to Achieve Opportunistic SRAM Voltage Switching in Dual-Supply Near-Threshold Processors