Helen: Maliciously secure coopetitive learning for linear models

S Sharma, C Xing, Y Liu, Y Kang - 2019 IEEE international …, 2019 - ieeexplore.ieee.org

Machine Learning models require a vast amount of data for accurate training. In reality, most
data is scattered across different organizations and cannot be easily integrated under many …

被引用次数：103 相关文章所有 6 个版本

[PDF] github.io

Encrypted cooperative control revisited

AB Alexandru, MS Darup… - 2019 IEEE 58th …, 2019 - ieeexplore.ieee.org

Distributed systems are ubiquitous in present-day technologies like smart cities. Such
applications require decentralized control, which reduces the load on a single central party …

被引用次数：39 相关文章所有 3 个版本

[PDF] jos.org.cn

机器学习中的隐私攻击与防御

刘睿瑄，陈红，郭若杨，赵丹，梁文娟，李翠平 - 软件学报, 2019 - jos.org.cn

大数据时代丰富的信息来源促进了机器学习技术的蓬勃发展, 然而机器学习模型的训练集在数据
采集, 模型训练等各个环节中存在的隐私泄露风险, 为人工智能环境下的数据管理提出了重大 …

被引用次数：8 相关文章所有 5 个版本

[PDF] github.io

Privacy-preserving collaborative medical time series analysis based on dynamic time warping

X Liu, X Yi - Computer Security–ESORICS 2019: 24th European …, 2019 - Springer

Evaluating medical time series (eg, physiological sequences) under dynamic time warping
(DTW) derives insights assisting biomedical research and clinical decision making. Due to …

被引用次数：14 相关文章所有 6 个版本

[PDF] berkeley.edu

[PDF][PDF] Towards privacy-preserving collaborative gradient boosted decision trees

C Leung, A Law, O Sima - UC Berkeley, 2019 - people.eecs.berkeley.edu

With the wide availability of data in recent years, machine learning has taken off as an
effective general solution with an abundance of use cases. Collaborative learning can yield …

被引用次数：13 相关文章

[PDF] gatech.edu

[PDF][PDF] Privacy-preserving deep learning with SPDZ

S Sharma, C Xing, Y Liu - The AAAI Workshop on Privacy …, 2019 - isye.gatech.edu

Neural Networks (NN) are powerful tools for supervised machine learning. However,
extensive data collection from different sources for accurate training risks privacy. Most …

被引用次数：8 相关文章

[PDF] jos.org.cn