CloudDLP: Transparent and Scalable Data Sanitization for Browser-Based Cloud Storage

doi:10.1109/ACCESS.2020.2985870

	CloudDLP: Transparent and Scalable Data Sanitization for Browser-Based Cloud Storage
	Han, Peiyi 1,2; Liu, Chuanyi 2,3; Cao, Jiahao 4; Duan, Shaoming 2; Pan, Hezhong 1; Cao, Zekun 5,6; Fang, Binxing 2,3
	2020
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	8 页码:68449-68459
摘要	Browser-based cloud storage services are still broadly used in enterprises for online sharing and collaboration. However, sensitive information in images or documents may be easily leaked outside trusted enterprise on-premises due to such cloud services. Existing solutions to prevent data leakage in cloud storage services either limit many functionalities of cloud applications or are difficult to be scaled to various cloud applications. In this paper, we propose CloudDLP, a transparent and scalable approach for enterprises to automatically sanitize sensitive data in images and documents with various browser-based cloud applications. CloudDLP is deployed as an internet gateway within the premises of an enterprise using JavaScript injecting techniques and deep learning methods to sanitize sensitive premise data. It neither compromises the user experience nor significantly affects application functionalities in browser-based cloud storage services. We have evaluated CloudDLP with a number of real-world cloud applications. Our experimental results show that it can achieve automatic data sanitization with cloud storage services while preserving most functionalities of cloud applications.
关键词	Cloud computing Machine learning Browsers Protocols Cryptography Electronic mail Data loss prevention data sanitization data security cloud storage
DOI	10.1109/ACCESS.2020.2985870
收录类别	SCI
语种	英语
资助项目	Key Research and Development Program for Guangdong Province[2019B010136001] ; National Key Research and Development Program of China[2016YFB0800803] ; National Key Research and Development Program of China[2018YFB1004005] ; National Natural Science Foundation of China[61872110]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000527419200007
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/15412
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liu, Chuanyi
作者单位	1.Beijing Univ Posts & Telecommun, Sch Cyberspace Secur, Beijing 100876, Peoples R China 2.Harbin Inst Technol Shenzhen, Sch Comp Sci & Technol, Shenzhen 518055, Peoples R China 3.Peng Cheng Lab, Shenzhen 518055, Peoples R China 4.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing 100190, Peoples R China 6.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Han, Peiyi,Liu, Chuanyi,Cao, Jiahao,et al. CloudDLP: Transparent and Scalable Data Sanitization for Browser-Based Cloud Storage[J]. IEEE ACCESS,2020,8:68449-68459.
APA	Han, Peiyi.,Liu, Chuanyi.,Cao, Jiahao.,Duan, Shaoming.,Pan, Hezhong.,...&Fang, Binxing.(2020).CloudDLP: Transparent and Scalable Data Sanitization for Browser-Based Cloud Storage.IEEE ACCESS,8,68449-68459.
MLA	Han, Peiyi,et al."CloudDLP: Transparent and Scalable Data Sanitization for Browser-Based Cloud Storage".IEEE ACCESS 8(2020):68449-68459.