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CNS Core: Small: Towards Secure-By-Design Integration of Emerging Non-Volatile Memory in Future Systems

CNS Core: Small: Towards Secure-By-Design Integration of Emerging Non-Volatile Memory in Future Systems
CNS 核心:小型:在未来系统中实现新兴非易失性存储器的安全设计集成
批准号:
2008339
负责人:
Fan Yao
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30

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中文摘要
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英文摘要
Computer systems are increasingly adopting Non-Volatile Memories (NVMs) that offer high capacity, superior power efficiency and persistent storage. Traditionally, tremendous effort has been made to address NVM security issues concerning the non-volatility property. However, the advent of hardware-based information leakage attacks necessities a systematic re-assessment of NVM memory architectures. This project is investigating the information security threats in the form of side and covert channels in computing systems where NVMs are integrated in different ways. A holistic examination of the security properties from device-level accesses to system-level management policies will be performed. Based on a comprehensive understanding of the potential attack vectors, this project will design efficient architecture and system level defensive techniques to defeat futuristic adversaries exploiting the discovered information leakage vulnerabilities in NVM-based systems. Towards this end, this project aims to bolster information security for systems with NVM integration from the following aspects: (1) Securing NVM as main memory; (2) Securing DRAM/NVM Hybrid Memory System; (3) Securing NVMs as Fast Storage Devices.As traditional memory technology faces severe scalability issues, NVMs are increasingly playing key roles in the whole storage stack of server systems such as data centers and high-performance computing infrastructures. In light of the advances in hardware-based security breaches, understanding and taming information leakage due to the architecture/system design for emerging NVM-enabled systems are imperative for the future large-scale adoption. This project is systematically evaluating information leakage threats in emerging NVM memory and storage systems. If successful, the project will enable secure integration of NVMs in computing systems that are resistant to information leakage attacks. The work will result in the dissemination of tools, attack libraries, software, and simulation results to the computer architecture and security community.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(6)
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科研奖励(0)
会议论文
DOI: 10.1145/3466752.3480054
发表时间: 2021-10
期刊: MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture
影响因子: --
作者: [Md Hafizul Islam Chowdhuryy;M. Rashed;Amro Awad;Rickard Ewetz;Fan Yao]
通讯作者: Md Hafizul Islam Chowdhuryy;M. Rashed;Amro Awad;Rickard Ewetz;Fan Yao
COMPACT: Flow-Based Computing on Nanoscale Crossbars with Minimal Semiperimeter and Maximum Dimension
COMPACT:具有最小半周长和最大尺寸的纳米级横杆上基于流的计算
DOI: 10.1109/tcad.2021.3138356
发表时间: 2021
期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
影响因子: 2.9
作者: [Thijssen, Sven, Jha, Sumit Kumar, Ewetz, Rickard]
通讯作者: Ewetz, Rickard
Seeds of SEED: R-SAW: New Side Channels Exploiting Read Asymmetry in MLC Phase Change Memories
SEED 的种子:R-SAW:利用 MLC 相变存储器中的读取不对称性的新侧通道
DOI: 10.1109/seed51797.2021.00013
发表时间: 2021
期刊: 2021 International Symposium on Secure and Private Execution Environment Design (SEED
影响因子: --
作者: [Chowdhuryy, Md Hafizul, Ewetz, Rickard, Awad, Amro, Yao, Fan]
通讯作者: Yao, Fan
DOI: 10.1109/hpca56546.2023.10070924
发表时间: 2023-02
期刊: 2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
影响因子: --
作者: [Md Hafizul Islam Chowdhuryy;Myoungsoo Jung;F. Yao;Amro Awad]
通讯作者: Md Hafizul Islam Chowdhuryy;Myoungsoo Jung;F. Yao;Amro Awad
6
    CAREER: Understanding and Ensuring Secure-by-design Microarchitecture in Modern Era of Computing
    Collaborative Research: SaTC: CORE: Small: Understanding and Taming Deterministic Model Bit Flip attacks in Deep Neural Networks
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