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Comprehensive Designs of Innovate Secure Hardware Devices Against Machine Learning Attacks and Power Analysis Attacks

机译：创新安全硬件设备对机器学习攻击和功率分析攻击的综合设计

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作者
?Wen, Yiming;
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作者单位

Old Dominion University;

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授予单位 Old Dominion University;
学科
学位 Ph.D.
年度 2020
页码 140 p.
总页数 140
原文格式 PDF
正文语种 eng
中图分类
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专利

1. Exploiting Machine Learning Against On-Chip Power Analysis Attacks: Tradeoffs and Design Considerations [J] . Kenarangi Farid, Partin-Vaisband Inna IEEE transactions on circuits and systems . I , Regular papers . 2019,第2期

机译：利用机器学习抵御片上功率分析攻击：权衡和设计考虑因素
2. Efficiently Secure ECC Scalar Multiplication Methods against Power Analysis Attacks on Resource Constrained Devices [J] . TURKI F. ALSOMANI, HILAL HOUSSAIN WSEAS Transactions on Computers . 2017,第Pta2期

机译：有效地保护ECC标量乘法方法对资源受限设备的功率分析攻击
3. Real-Time Detection of Power Analysis Attacks by Machine Learning of Power Supply Variations On-Chip [J] . Utyamishev Dmitry, Partin-Vaisband Inna IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems . 2020,第1期

机译：电源变化机器学习电源变化的功率分析攻击的实时检测
4. EQZ-LDO: A Near-Zero EDP Overhead, >10M-Attack-Resilient, Secure Digital LDO featuring Attack-Detection and Detection-Driven Protection for a Correlation-Power-Analysis-Resilient IoT Device [C] . Sung Justin Kim, Dongkwun Kim, Ayushparth Sharma, Symposium on VLSI Circuits . 2021

机译：EQZ-LDO：近零EDP开销，> 10M攻击 - 弹性，安全数字LDO，具有攻击检测和检测驱动的保护，用于相关 - 功率分析 - 弹性IOT设备
5. Machine Learning for the Analysis of Power System Loads: Cyber-Attack Detection and Generation of Synthetic Datasets [D] . Pinceti, Andrea. 2021

机译：电力系统负载分析的机器学习：网络攻击检测和合成数据集的产生
6. An Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks [O] . Andrew Churcher, Rehmat Ullah, Jawad Ahmad, 2021

机译：IOT网络中机器学习攻击分类的实验分析
7. Power analysis attack against encryption devices: a comprehensive analysis of AES, DES, and BC3 [O] . Septafiansyah Dwi Putra, Mario Yudhiprawira, Sarwono Sutikno, 2019

机译：对加密设备的功率分析攻击：对AES，DES和BC3的综合分析

Comprehensive Designs of Innovate Secure Hardware Devices Against Machine Learning Attacks and Power Analysis Attacks

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