Privacy-preserving efficient searchable encryption

Data storage and computation outsourcing to third-party managed data centers, in environments such as Cloud Computing, is increasingly being adopted by individuals, organizations, and governments. However, as cloud-based outsourcing models expand to society-critical data and services, the lack of effective and independent control over security and privacy conditions in such settings presents significant challenges. An interesting solution to these issues is to perform computations on encrypted data, directly in the outsourcing servers. Such an approach benefits from not requiring major data transfers and decryptions, increasing performance and scalability of operations. Searching operations, an important application case when cloud-backed repositories increase in number and size, are good examples where security, efficiency, and precision are relevant requisites. Yet existing proposals for searching encrypted data are still limited from multiple perspectives, including usability, query expressiveness, and client-side performance and scalability. This thesis focuses on the design and evaluation of mechanisms for searching encrypted data with improved efficiency, scalability, and usability. There are two particular concerns addressed in the thesis: on one hand, the thesis aims at supporting multiple media formats, especially text, images, and multimodal data (i.e. data with multiple media formats simultaneously); on the other hand the thesis addresses client-side overhead, and how it can be minimized in order to support client applications executing in both high-performance desktop devices and resource-constrained mobile devices. From the research performed to address these issues, three core contributions were developed and are presented in the thesis: (i) CloudCryptoSearch, a middleware system for storing and searching text documents with privacy guarantees, while supporting multiple modes of deployment (user device, local proxy, or computational cloud) and exploring different tradeoffs between security, usability, and performance; (ii) a novel framework for efficiently searching encrypted images based on IES-CBIR, an Image Encryption Scheme with Content-Based Image Retrieval properties that we also propose and evaluate; (iii) MIE, a Multimodal Indexable Encryption distributed middleware that allows storing, sharing, and searching encrypted multimodal data while minimizing client-side overhead and supporting both desktop and mobile devices

A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage

Security has become a significant concern with the increased popularity of cloud storage services. It comes with the vulnerability of being accessed by third parties. Security is one of the major hurdles in the cloud server for the user when the user data that reside in local storage is outsourced to the cloud. It has given rise to security concerns involved in data confidentiality even after the deletion of data from cloud storage. Though, it raises a serious problem when the encrypted data needs to be shared with more people than the data owner initially designated. However, searching on encrypted data is a fundamental issue in cloud storage. The method of searching over encrypted data represents a significant challenge in the cloud. Searchable encryption allows a cloud server to conduct a search over encrypted data on behalf of the data users without learning the underlying plaintexts. While many academic SE schemes show provable security, they usually expose some query information, making them less practical, weak in usability, and challenging to deploy. Also, sharing encrypted data with other authorized users must provide each document's secret key. However, this way has many limitations due to the difficulty of key management and distribution. We have designed the system using the existing cryptographic approaches, ensuring the search on encrypted data over the cloud. The primary focus of our proposed model is to ensure user privacy and security through a less computationally intensive, user-friendly system with a trusted third party entity. To demonstrate our proposed model, we have implemented a web application called CryptoSearch as an overlay system on top of a well-known cloud storage domain. It exhibits secure search on encrypted data with no compromise to the user-friendliness and the scheme's functional performance in real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table

Privacy preserving and serverless homomorphic-based searchable encryption as a service (SEaaS)

Serverless computing has seen rapid growth, thanks to its adaptability, elasticity, and deployment agility, embraced by both cloud providers and users. However, this surge in serverless adoption has prompted a reevaluation of security concerns and thus, searchable encryption has emerged as a crucial technology. This paper explores the Searchable Encryption as a Service (SEaaS) and introduces an innovative privacy-preserving Multiple Keyword Searchable Encryption (MKSE) scheme within a serverless cloud environment, addressing previously unmet security goals. The proposed scheme employs probabilistic encryption and leverages fully homomorphic encryption to enable operations on ciphertext, facilitating searches on encrypted data. Its core innovation lies in the use of probabilistic encryption for private multi-keyword searches. To validate its practicality, we deploy the scheme on the public cloud infrastructure, “Contabo,” and conduct rigorous testing on a real-world dataset. The results demonstrate that our novel scheme successfully preserves the privacy of search queries and access patterns, achieving robust security. This research contributes to the field of serverless cloud security, particularly in the context of searchable encryption, by providing a refined solution for safeguarding data while maintaining usability in a serverless computing landscape

Achieving Fine-grained Multi-keyword Ranked Search over Encrypted Cloud Data

With the advancement of Cloud computing, people now store their data on remote Cloud servers for larger computation and storage resources. However, users’ data may contain sensitive information of users and should not be disclosed to the Cloud servers. If users encrypt their data and store the encrypted data in the servers, the search capability supported by the servers will be significantly reduced because the server has no access to the data content. In this paper, we propose a Fine-grained Multi-keyword Ranked Search (FMRS) scheme over encrypted Cloud data. Specifically, we leverage novel techniques to realize multikeyword ranked search, which supports both mixed “AND”, “OR” and “NO” operations of keywords and ranking according to the preference factor and relevance score. Through security analysis, we can prove that the data confidentiality, privacy protection of index and trapdoor, and the unlinkability of trapdoor can be achieved in our FMRS. Besides, Extensive experiments show that the FMRS possesses better performance than existing schemes in terms of functionality and efficiency

M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices

Searchable Encryption (SE) allows mobile devices with limited computing and storage resources to outsource data to an untrusted cloud server. Users are able to search and retrieve the outsourced, however, it suffers from information and privacy leakage. The reason is that most of the previous works rely on the single cloud model, which allows that the cloud server get all the search information from users. In this paper, we present a new scheme M-SSE that achieves both forward and backward security based on a multi-cloud technique. The new scheme is secure against both adaptive file injection attack and size pattern attack by utilizing multiple cloud servers. Experiment results show that our scheme is effective compared with the other existing schemes

Offline privacy preserving proxy re-encryption in mobile cloud computing

This paper addresses the always online behavior of the data owner in proxy re- encryption schemes for re-encryption keys issuing. We extend and adapt multi-authority ciphertext policy attribute based encryption techniques to type-based proxy re-encryption to build our solution. As a result, user authentication and user authorization are moved to the cloud server which does not require further interaction with the data owner, data owner and data users identities are hidden from the cloud server, and re-encryption keys are only issued to legitimate users. An in depth analysis shows that our scheme is secure, flexible and efficient for mobile cloud computing