Collaborative Research: SaTC: CORE: Medium: Hardware Security Insights: Analyzing Hardware Designs to Understand and Assess Security Weaknesses and Vulnerabilities

协作研究:SaTC:核心:中:硬件安全见解:分析硬件设计以了解和评估安全弱点和漏洞

基本信息

  • 批准号:
    2247755
  • 负责人:
  • 金额:
    $ 57.1万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-07-01 至 2027-06-30
  • 项目状态:
    未结题

项目摘要

This project’s goal is to develop better methods for understanding how information flows in computer hardware designs, and thus increase their security. The microprocessors, wireless modems, graphics processing units, and other hardware components at the heart of all computing devices are designed by engineers using low-level hardware description languages. These designs are complex, making it difficult to reason about security vulnerabilities that may allow attackers to extract valuable secret information like cryptographic keys and personally identifiable information. Hardware security verification aims to identify hardware weaknesses, patch potential vulnerabilities, and mitigate the harm of attacks. Understanding how information flows in hardware designs can help verification engineers to assess whether secret data can be extracted by an attacker and to develop designs that prevent those vulnerable flows.The project is structured around three main aims that together will lead to improved tools for insights around hardware information flow tracking. The first aim is to automate the generation of information-flow properties, which can then be verified by existing tools. The second is to develop testbenches that fully exercise possible information flows through a design, using angelic execution oracles designed to maximize coverage of possible information flows. The third is to develop a new “hyperflow analysis” framework that provides both analytic representations to support algorithms for hardware design and verification, and visual representations that help verification engineers explore hardware vulnerabilities through an information-flow lens. The work will involve a number of undergraduate and graduate students, contributing to the development of the computer security workforce.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.
该项目是为了理解计算机硬件设计中的流动方法复杂的是,很难推理toat的安全漏洞,这可能会使铲球可以提取诸如密码和个人信息之类的秘密信息,以识别硬件弱点,补丁潜在的脆弱性,并察觉到硬件设计中的烦恼如何帮助验证工程师评估数据由攻击者提取并开发脆弱流动的设计。该项目围绕三个主要目的,这些目标共同导致改进的工具福特软件信息流跟踪。第二个是开发通过Desigha Desigh Desigh Desigh Desigh Desigh的测试板,使用天使般的执行来最大程度地覆盖可能的信息流量。硬件脆弱性工作于工作人员和毕业生的工作人员安全劳动力。该奖项反映了NSF'Stutory Mission,值得支持Thalugh评估我们的优点和更广泛的影响。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Isadora: automated information-flow property generation for hardware security verification
  • DOI:
    10.1007/s13389-022-00306-w
  • 发表时间:
    2022-11
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    Calvin Deutschbein;Andres Meza;Francesco Restuccia;R. Kastner;C. Sturton
  • 通讯作者:
    Calvin Deutschbein;Andres Meza;Francesco Restuccia;R. Kastner;C. Sturton
Special Session: CAD for Hardware Security - Promising Directions for Automation of Security Assurance
  • DOI:
    10.1109/vts56346.2023.10140100
  • 发表时间:
    2023-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sohrab Aftabjahani;M. Tehranipoor;Farimah Farahmandi;Bulbul Ahmed;R. Kastner;Francesco Restuccia;Andres Meza;Kaki Ryan;Nicole Fern;J. V. Woudenberg;Rajesh Velegalati;Cees-Bart Breunesse;C. Sturton;Calvin Deutschbein
  • 通讯作者:
    Sohrab Aftabjahani;M. Tehranipoor;Farimah Farahmandi;Bulbul Ahmed;R. Kastner;Francesco Restuccia;Andres Meza;Kaki Ryan;Nicole Fern;J. V. Woudenberg;Rajesh Velegalati;Cees-Bart Breunesse;C. Sturton;Calvin Deutschbein
Automated Generation, Verification, and Ranking of Secure SoC Access Control Policies
安全 SoC 访问控制策略的自动生成、验证和排序
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Ryan Kastner其他文献

TOP: Towards Open & Predictable Heterogeneous SoCs
顶部:走向开放
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Luca Valente;Francesco Restuccia;Davide Rossi;Ryan Kastner;Luca Benini
  • 通讯作者:
    Luca Benini
Gate-Level Information Flow Tracking for Security Lattices
安全网格的门级信息流跟踪
FKeras: A Sensitivity Analysis Tool for Edge Neural Networks
FKeras:边缘神经网络的敏感性分析工具
Mangrove Ecosystem Detection using Mixed-Resolution Imagery with a Hybrid-Convolutional Neural Network
使用混合分辨率图像和混合卷积神经网络进行红树林生态系统检测
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dillon Hicks;Ryan Kastner;C. Schurgers;Astrid Hsu;Octavio Aburto
  • 通讯作者:
    Octavio Aburto
Behavioral Synthesis for Hardware Security
硬件安全的行为综合
  • DOI:
    10.1007/978-3-030-78841-4
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Srinivas Katkoori;Omkar Dokur;Rajeev Joshi;Kavya Lakshmi Kalyanam;Md Adnan Zaman;Ariful Islam;Nandeesha Veeranna;Benjamin Carrion Schafer;Rajat Pranesh Santikellur;Subhra Chakraborty;S. Bhunia;Hannah Badier;Jean;Philippe Coussy;Guy Gogniat;C. Pilato;D. Sciuto;Francesco Regazzoni;Siddharth Garg;Ramesh Karri;Anirban Sengupta;Mahendra Rathor;Matthew Lewandowski;Chen Liu;Chengmo Yang;Farhath Zareen;Robert Karam;S. T. C. Konigsmark;Wei Ren;Martin D. F. Wong;Deming Chen;Mike Borowczak;Ranga Vemuri;Steffen Peter;T. Givargis;Wei Hu;Armaiti Ardeshiricham;Lingjuan Wu;Ryan Kastner;Christian Pilato Politecnico;di Milano;Italy Milan;ST Micro;Singapore Singapore;S. Islam
  • 通讯作者:
    S. Islam

Ryan Kastner的其他文献

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{{ truncateString('Ryan Kastner', 18)}}的其他基金

REU Site: Engineers for Exploration
REU 站点:勘探工程师
  • 批准号:
    2244123
  • 财政年份:
    2023
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
REU Site: Engineers for Exploration
REU 站点:勘探工程师
  • 批准号:
    1852403
  • 财政年份:
    2019
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
Student Travel Support for the International Symposium on Hardware-Oriented Security and Trust (HOST)
面向硬件的安全与信任国际研讨会 (HOST) 的学生旅行支持
  • 批准号:
    1830895
  • 财政年份:
    2018
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
SaTC: STARSS: Small: Property Driven Hardware Security
SaTC:STARSS:小型:财产驱动的硬件安全
  • 批准号:
    1718586
  • 财政年份:
    2017
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
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
  • 财政年份:
    2016
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Continuing Grant
REU Site: Engineers for Exploration
REU 站点:勘探工程师
  • 批准号:
    1560162
  • 财政年份:
    2016
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
TWC: Small: Employing Information Theoretic Metrics to Quantify and Enhance the Security of Hardware Designs
TWC:小型:采用信息论指标来量化和增强硬件设计的安全性
  • 批准号:
    1527631
  • 财政年份:
    2015
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
I-Corps: Provable Hardware Design for Integrity and Security
I-Corps:可证明的硬件设计的完整性和安全性
  • 批准号:
    1339522
  • 财政年份:
    2013
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
REU Site: Engineers for Exploration
REU 站点:勘探工程师
  • 批准号:
    1263320
  • 财政年份:
    2013
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant
SHF: Medium: Collaborative Research: Building Critical Systems with Verifiable Properties Using Gate Level Analysis
SHF:中:协作研究:使用门级分析构建具有可验证属性的关键系统
  • 批准号:
    1162177
  • 财政年份:
    2012
  • 资助金额:
    $ 57.1万
  • 项目类别:
    Standard Grant

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相似海外基金

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合作研究:SaTC:核心:中:使用智能会话代理使青少年能够抵御网络诱骗
  • 批准号:
    2330940
  • 财政年份:
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  • 资助金额:
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Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317232
  • 财政年份:
    2024
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    $ 57.1万
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    Continuing Grant
Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338301
  • 财政年份:
    2024
  • 资助金额:
    $ 57.1万
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Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317233
  • 财政年份:
    2024
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    $ 57.1万
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Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
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