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MRI: Acquisition of High-Resolution Photon Emission/Laser Fault Injection Microscope with High-Performance Computers for Failure Analysis and Security Assessment of Electronic Syst

MRI: Acquisition of High-Resolution Photon Emission/Laser Fault Injection Microscope with High-Performance Computers for Failure Analysis and Security Assessment of Electronic Syst
MRI:使用高性能计算机获取高分辨率光子发射/激光故障注入显微镜,用于电子系统的故障分析和安全评估
批准号:
2117349
负责人:
Fatemeh Ganji
金额:
$36.06万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-08-15 至 2024-07-31

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中文摘要
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英文摘要
This MRI acquisition project will allow the purchase of a high-resolution Photon Emission/Laser Fault Injection microscope and high-performance computers. This setup will provide a platform for research, teaching, and hands-on experience for students and industry professionals. The research this instrumentation will enable focuses on the performance and security analyses of electronic devices and systems at different stages of their lifetime which will address a critical issue, securing the integrated circuit (IC) supply chain. The project has the potential to secure large number of devices used across sensitive applications, such as in healthcare, artificial intelligence (AI), finance, transportation, and defense. With a user-friendly interface, the instrument is expected to maximize the accessibility for on-site and off-campus students and researchers. The data collected from this setup will be further made available as benchmarks to researchers in the field of AI and cybersecurity. The instrument will bring unique capabilities to the PIs’ institution and surrounding areas to conduct research, education, and outreach activities on IC security. The PIs plan to educate and train students through online and on-site courses, as well as seminars and workshops. The PIs plan to promote broadening the participation in this research area, especially recruitment of female students. The MRI instrument is expected to facilitate research geared to the needs of the semiconductor industry, especially with the focus on security and reliability of ICs, including three interdisciplinary topics, IC tampering and counterfeiting detection, security testing and design for security, and security evaluation using AI. The common factor among these themes is the requirement for an advanced optical mechanism to interact with an integrated circuit at the scale of a single or a handful of transistors in a non-destructive fashion. While the first topic addresses the attacks that can be mounted during the pre- and post-fabrication, the second topic aims to provide a framework for testing and certifying a chip after manufacturing and designing a more secure chip. To achieve the goals defined in these themes, in the third topic, AI acts as an enabler since its essential role is to help analyze the data more efficiently and extract more in-depth and comprehensive information to back methodologies in the prior topics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
Self-timed Sensors for Detecting Static Optical Side Channel Attacks
用于检测静态光学侧信道攻击的自定时传感器
DOI: --
发表时间: 2022
期刊: International Symposium on Quality Electronic Design
影响因子: --
作者: [Roy, Sourav, Farheen, Tasnuva, Tajik, Shahin, Forte, Domenic]
通讯作者: Forte, Domenic
Threat Modeling and Risk Analysis for Miniaturized Wireless Biomedical Devices
小型无线生物医学设备的威胁建模和风险分析
DOI: 10.1109/jiot.2022.3144130
发表时间: 2022
期刊: IEEE Internet of Things Journal
影响因子: 10.6
作者: [Vakhter, Vladimir, Soysal, Betul, Schaumont, Patrick, Guler, Ulkuhan]
通讯作者: Guler, Ulkuhan
DOI: 10.1145/3560828.3564010
发表时间: 2022-11
期刊: Proceedings of the 9th ACM Workshop on Moving Target Defense
影响因子: --
作者: [D. Koblah;F. Ganji;Domenic Forte;Shahin Tajik]
通讯作者: D. Koblah;F. Ganji;Domenic Forte;Shahin Tajik
DOI: 10.46586/tches.v2023.i1.301-325
发表时间: 2022-11
期刊: IACR Trans. Cryptogr. Hardw. Embed. Syst.
影响因子: --
作者: [Tahoura Mosavirik;P. Schaumont;Shahin Tajik]
通讯作者: Tahoura Mosavirik;P. Schaumont;Shahin Tajik
ERI: Foundations of Machine Learning for Side-channel Analysis
  • 批准号:
    2138420
  • 项目类别:
    Standard Grant
  • 资助金额:
    $19.47万
  • 财政年份:
    2022
  • 负责人:
    Fatemeh Ganji
  • 依托单位:
海外基金