In a cloud storage system, to allow searching over encrypted data by the cloud server, searchable symmetric encryption (SSE) has been proposed in the literature. The basic security requirement of SSE is that the cloud server learns no information about the files or keywords during the searching process. Some SSE schemes also offer additional functionalities such as detecting cheating behaviour of a malicious server (i.e., verifiability) and allowing update (e.g., modifying, deleting and adding) of documents on the server. However, the previous (verifiable) SSE schemes were mainly designed for single users, which means the searching can only be done by the data owner, whereas in reality people often use cloud storage to share files with other users. In this paper we present a multi-user verifiable searchable symmetric encryption (MVSSE) scheme that achieves all the desirable features of a verifiable SSE and allows multiple users to perform searching. We then define an ideal functionality for MVSSE under the Universally Composable (UC-) security framework and prove that our ideal functionality implies the security requirements of a secure MVSSE, and our multi-user verifiable SSE scheme is UC-secure. We also implement our scheme to verify its high performance based on some real dataset.

As cloud storage has been widely adopted in various applications, how to protect data privacy while allowing efficient data search and retrieval in a distributed environment remains a challenging research problem. Existing searchable encryption schemes are still inadequate on desired functionality and security/privacy perspectives. Specifically, supporting multi-keyword search under the multi-user setting, hiding search pattern and access pattern, and resisting keyword guessing attacks (KGA) are the most challenging tasks. In this article, we present a new searchable encryption scheme that addresses the above problems simultaneously, which makes it practical to be adopted in distributed systems. It not only enables multi-keyword search over encrypted data under a multi-writer/multi-reader setting but also guarantees the data and search pattern privacy. To prevent KGA, our scheme adopts a multi-server architecture, which accelerates search response, shares the workload, and lowers the key leakage risk by allowing only authorized servers to jointly test whether a search token matches a stored ciphertext. A novel subset decision mechanism is also designed as the core technique underlying our scheme and can be further used in applications other than keyword search. Finally, we prove the security and evaluate the computational and communication efficiency of our scheme to demonstrate its practicality.

As the next-generation power grid, the smart grid has significantly improved dependability, flexibility, and efficiency compared with the traditional power grid. However, due to increasingly diverse application requirements, it faces challenges on balancing data privacy, efficiency, and robustness. In this paper, we present a fog computing-based smart grid model. In addition, based on the proposed model, we construct an efficient and privacy-preserving scheme that supports malicious secure smart grid usage data aggregation communication. To our best knowledge, this is the first concrete smart grid solution that concurrently achieves secure aggregation communication, data privacy, and data robustness (e.g., false data detection). Specifically, benefiting from Boolean/Arithmetic secret-sharing methods, our proposed scheme allows home users to report their electricity usage data to the cloud and fogs securely. Besides, a false data detection protocol is proposed to resist false data injection attacks launched by malicious home users. Theoretical analysis and experimental implementation show that our scheme efficiently achieves data security, anonymity, and robustness.

Message-Locked Encryption (MLE) is a useful tool to enable deduplication over encrypted data in cloud storage. It can significantly improve the cloud service quality by eliminating redundancy to save storage resources, and hence user cost, and also providing defense against different types of attacks, such as duplicate faking attack and brute-force attack. A typical MLE scheme only focuses on deduplication. On the other hand, supporting search operations on stored content is another essential requirement for cloud storage. In this paper, we present a message-locked searchable encryption (MLSE) scheme in a dual-server setting, which achieves simultaneously the desirable features of supporting deduplication and enabling users to perform search operations over encrypted data. In addition, it supports both multi-keyword and negative keyword searches. We formulate the security notions of MLSE and prove our scheme satisfies all the security requirements. Moreover, we provide an interesting extension of our construction to support Proof of Storage (PoS). Compared with the existing solutions, MLSE achieves better functionalities and efficiency, and hence enables more versatile and efficient cloud storage service.

With the prevalence of outsourced computation, such as Machine Learning as a Service, protecting the privacy of sensitive data throughout the whole computation is a critical yet challenging task. The problem becomes even more tricky when multiple sources of input and/or multiple recipients of output are involved, who would encrypt/decrypt data using different keys. Considering many computation tasks demand binary operands and operations but there are only outsourced computation constructions for arithmetic calculations [1], in this paper, the authors propose a privacy-preserving outsourced computation framework for Boolean circuits. The proposed framework can protect sensitive data throughout the whole computation, i.e., input, output and all the intermediate values, ensuring privacy for general outsourced tasks. Moreover, it compresses the ciphertext domain of [1] and attains secure protocols for four logic gates (AND, OR, NOT, and XOR) which are the basic operations in Boolean circuits. With the proposed framework as a building block, a novel Privacy-preserved (encrypted) Bloom Filter and a Multi-keyword Searchable Encryption scheme under the multi-user setting are presented. Security proof and experimental results show that the proposal is reliable and practical.