Public key Encryption with Keyword Search (PEKS) has emerged as a solution for the receiver to securely search the sender’s encrypted data on the cloud. However, the PEKS scheme is threatened by the Keyword Guessing Attack (KGA), which leaks the receiver’s keyword privacy. To resist KGA, researchers have inherited the authentication mechanism into the PEKS system (PAEKS) but also forbid using one trapdoor to search all sender’s encrypted data. In this paper, we explore the KGA problem from grouping senders and propose the notion of Identity-based Group Encryption with Keyword Search (IBGEKS), which leverages Identity-based cryptography to securely search encrypted data. Compared with the PAEKS scheme, the IBGEKS scheme can search the sender’s ciphertexts within the same group established by the receiver via one receiver’s trapdoor. For security, we analyze the KGA problem and propose ciphertexts, identities, and trapdoors indistinguishability for IBGEKS. The evaluation depicts that the IBGEKS has competitive algorithm performance with other SA-PEKS and PAEKS schemes and has superior search performance on the Enron email dataset.

It has become a trend for clients to outsource their encrypted databases to remote servers and then leverage the Searchable Encryption technique to perform secure data retrieval. However, the method has yet to be considered a crucial need for replication on searchable encrypted data. It calls for challenging works on Dynamic Searchable Symmetric Encryption (DSSE) since clients must share the search capability of the encrypted data replicas and guarantee forward and backward privacy. We define a new notion called “Keyword Search Shareable Encryption” (KS2E) and the corresponding security model capturing forward and backward privacy. In our notion, data owners are allowed to share search indexes of the encrypted data with users. A search index will be updated with a new search key before sharing to guarantee the data privacy of the source database. The target database also inherits data search efficiency along with the shared data. We further construct an instance of KS2E calledBranch, prove its security, and use real-world datasets to evaluate Branch. The evaluation results show that Branch’s performance is comparable to classical DSSE schemes on search efficiency and demonstrate the effectiveness on searching encrypted data replicas from multiple owners.

For the industrial Internet of Things (IIoT), public-key encryption with keyword search (PEKS) is a type of applicable and promising encryption technique to maintain the data stored in clouds secure and searchable. To further improve the efficiency of searching, it is popular to introduce edge computing near the IIoT as the substitute for a cloud. However, the straightforward collaboration of the two techniques performs negatively in latency-sensitive applications since the sluggish encryption of PEKS by IIoT devices negates the instant reaction of edges. To meet this challenge, in this article, we exploit the capability of the edge-cloud architecture and propose a lightweight-designed scheme called edge-aided searchable public-key encryption (ESPE). It allows IIoT devices to delegate their costly cryptographic operations to the nearby edge for fast computing and guarantees that all outsourced ciphertexts are semantically secure. Consequently, ESPE accelerates the corresponding ciphertext procedures on edges and saves over 70% encryption cost of an IIoT device.