中国科学技术大学学报最新文献_第5页

Visible light induced Barton decarboxylation free of radical initiators 可见光诱导无自由基引发剂的Barton脱羧

中国科学技术大学学报 Pub Date : 2020-11-30 DOI: 10.3969/J.ISSN.0253-2778.2020.11.004

Wang Jiaxin, Fu Mingchen

引用次数: 1

Zn(II)配位脂质体用于高效且血清耐受的基因转染 Zn(II)配位脂质体用于高效且血清耐受的基因转染

中国科学技术大学学报 Pub Date : 2020-11-30 DOI: 10.3969/J.ISSN.0253-2778.2020.11.003

Elbayomi Smaher M 聂旋邵琪王海利王飞尤业字周晓红

引用次数: 0

Recent achievements in solution processed antimony selenosulfide solar cells 溶液法处理硒化锑太阳能电池的最新进展

Journal of University of Science and Technology of China Pub Date : 2020-11-30 DOI: 10.3969/J.ISSN.0253-2778.2020.11.002

Jia Chenhui, Tang Rongfeng, Zhu Changfei, Chen Tao

引用次数: 0

Optimal time-locked trial strategy for software in the presence of piracy 存在盗版情况下软件的最优时效审判策略

Journal of University of Science and Technology of China Pub Date : 2020-10-31 DOI: 10.3969/J.ISSN.0253-2778.2020.10.004

Yang Feng, Lang Xiudong, A. Sheng

引用次数: 0

Adversarial attack based countermeasures against deep learning side-channel attacks 基于对抗性攻击的对抗深度学习侧信道攻击的对策

中国科学技术大学学报 Pub Date : 2020-10-31 DOI: 10.3969/J.ISSN.0253-2778.2020.10.006

Gu Ruizhe, Wang Ping, Zheng Mengce, Hu Honggang, Yu Nenghai

{"title":"Adversarial attack based countermeasures against deep learning side-channel attacks","authors":"Gu Ruizhe, Wang Ping, Zheng Mengce, Hu Honggang, Yu Nenghai","doi":"10.3969/J.ISSN.0253-2778.2020.10.006","DOIUrl":"https://doi.org/10.3969/J.ISSN.0253-2778.2020.10.006","url":null,"abstract":"Numerous previous works have studied deep learning algorithms applied in the context of side-channel attacks, which demonstrated the ability to perform successful key recoveries. These studies show that modern cryptographic devices are increasingly threatened by side-channel attacks with the help of deep learning. However, the existing countermeasures are designed to resist classical side-channel attacks, and cannot protect cryptographic devices from deep learning based side-channel attacks. Thus, there arises a strong need for countermeasures against deep learning based side-channel attacks. Although deep learning has the high potential in solving complex problems, it is vulnerable to adversarial attacks in the form of subtle perturbations to inputs that lead a model to predict incorrectly. \u0000In this paper, we propose a kind of novel countermeasures based on adversarial attacks that is specifically designed against deep learning based side-channel attacks. We estimate several models commonly used in deep learning based side-channel attacks to evaluate the proposed countermeasures. It shows that our approach can effectively protect cryptographic devices from deep learning based side-channel attacks in practice. In addition, our experiments show that the new countermeasures can also resist classical side-channel attacks.","PeriodicalId":17548,"journal":{"name":"中国科学技术大学学报","volume":"37 1","pages":"1343"},"PeriodicalIF":0.0,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91310751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Bayesian variable selection for proportional hazards model with current status data 基于当前状态数据的比例风险模型贝叶斯变量选择

Journal of University of Science and Technology of China Pub Date : 2020-10-31 DOI: 10.3969/J.ISSN.0253-2778.2020.10.003

Cui Di, Z. Weiping

引用次数: 0

A literature review of enterprise green transformation from the perspective of complex social network and prospects 复杂社会网络视角下企业绿色转型的文献综述与展望

Journal of University of Science and Technology of China Pub Date : 2020-10-31 DOI: 10.3969/J.ISSN.0253-2778.2020.10.005

Wan Liang, Fan Wenpei, Wang Chengyuan, Wang Shanyong

引用次数: 1

Sampling multivariate count variables with prespecified Pearson correlation using marginal regular vine copulas 抽样多元计数变量与预先指定的Pearson相关使用边际规则藤copula

中国科学技术大学学报 Pub Date : 2020-10-31 DOI: 10.3969/J.ISSN.0253-2778.2020.10.002

Yu Zhenfei, H. Taizhong