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Because cloud storage services have been broadly used in enterprises for online sharing and collaboration, sensitive information in images or documents may be easily leaked outside the trust enterprise on-premises due to such cloud services. Existing solutions to this problem have not fully explored the tradeoffs among application performance, service scalability, and user data privacy. Therefore, we propose CloudDLP, a generic approach for enterprises to automatically sanitize sensitive data in images and documents in browser-based cloud storage. To the best of our knowledge, CloudDLP is the first system that automatically and transparently detects and sanitizes both sensitive images and textual documents without compromising user experience or application functionality on browser-based cloud storage. To prevent sensitive information escaping from on-premises, CloudDLP utilizes deep learning methods to detect sensitive information in both images and textual documents. We have evaluated the proposed method on a number of typical cloud applications. Our experimental results show that it can achieve transparent and automatic data sanitization on the cloud storage services with relatively low overheads, while preserving most application functionalities. 

While cloud storage has become a common practice for more and more organizations, many severe cloud data breaches in recent years show that protecting sensitive data in the cloud is still a challenging problem. Although various mitigation techniques have been proposed, they are not scalable for large scale enterprise users with strict security requirements or often depend on error-prone human interventions. To address these issues, we propose FileCrypt, a generic proxy-based technique for enterprise users to automatically secure sensitive files in browser-based cloud storage. To the best of our knowledge, FileCrypt is the first attempt towards transparent and fully automated file encryption for browser-based cloud storage services. More importantly, it does not require active cooperations from cloud providers or modifications of existing cloud applications. By instrumenting mandatory file-related JavaScript APIs in browsers, FileCrypt can naturally support new cloud storage services and guarantee the file encryption cannot be bypassed. We have evaluated the efficacy of FileCrypt on a number of popular realworld cloud storage services. The results show that it can protect files on the public cloud with relatively low overheads. 

Searchable Encryption (SE) has been extensively examined by both academic and industry researchers. While many academic SE schemes show provable security, they usually expose some query information (e.g., search patterns) to achieve high efficiency. However, several inference attacks have exploited such leakage, e.g., a query recovery attack can convert opaque query trapdoors to their corresponding keywords based on some prior knowledge. On the other hand, many proposed SE schemes require significant modification of existing applications, which makes them less practical, weak in usability, and difficult to deploy. In this paper, we introduce a secure and practical SE scheme with provable security strength for cloud applications, called IDCrypt, which improves the search efficiency and enhanced the security strength of SE using symmetric cryptography. We further point out the main challenges in securely searching on multiple indexes and sharing encrypted data between multiple users. To address the above issues, we propose a token-adjustment scheme to preserve the search functionality among multi-indexes, and a key sharing scheme which combines Identity-Based Encryption (IBE) and Public-Key Encryption (PKE). Our experimental results show that the overhead of IDCrypt is fairly low.