We introduce the notion of committed vector oblivious linear evaluation (C-VOLE), which allows a party holding a pre-committed vector to generate VOLE correlations with multiple parties on the committed value. It is a unifying tool that can be found useful in zero-knowledge proofs (ZKPs) of committed values, actively secure multi-party computation, private set intersection (PSI), etc.

Content sharing, whether in Online Social Networks (OSNs) or even in the Internet of Things (IoT), serves as a pivotal link in the flow of data. To better protect the privacy of shared content, current OSNs allow sharers to manually set policies for uploaded content. However, this method of policy setting is not suitable for scenarios where IoT is deeply integrated with OSNs, as IoT devices often share content frequently and automatically. To address this issue, we propose the design, implementation, and evaluation of SmartCircles, a personalized photo-sharing and automatic deletion scheme. SmartCircles can function as a plugin within existing OSNs, supporting operations on various smart devices. It encompasses the following steps: a) Before sharing a photo, calculate the intimacy level depicted in the photo and the sharer's willingness to share. b) Before the recipient views the photo, calculate the intimacy between the sharer and the recipient, and evaluate feedback from the recipient. c) Based on the results computed above and a trade-off between profit and loss, recommend a recipient-aware automatic deletion control policy for the photo. We implement a prototype of SmartCircles, and the evaluation results demonstrate its effectiveness with an accuracy rate of policy recommendations reaching approximately 92%.

Private set intersection (PSI) allows two parties to compute the intersection of their sets without revealing anything else. In some applications of PSI, a server holds a large set and runs a PSI protocol with multiple clients, each with its own smaller set. In this setting, existing protocols fall short: they either achieve only semi-honest security, or else require the server to run the protocol from scratch for each execution.

Device-to-device (D2D) communication, as a traffic offloading technology in the fifth-generation (5G) network, can be widely used in several scenarios to provide 5G characteristics of higher speed, lower latency, and larger capacity. D2D data transmission over wireless channels among mobile devices is vulnerable to security threats and privacy violations from third parties and relay nodes. However, academia and industry have yet to propose relevant schemes or standards for D2D relay data transmission scenarios. We first propose a generic construction for D2D relay communication in this paper. Then, a concrete anonymous and secure D2D data transmission scheme with trajectory tracking is presented based on Chebyshev polynomials, hash-based message authentication code, and symmetric encryption. We employ a formal verification tool -Tamarin, modal logic analysis -BAN logic, and informal security analysis to demonstrate the security features of the proposed scheme. The performance evaluation shows that the proposed scheme can achieve desirable efficiency compared with other related schemes. Finally, we developed an APP‘, D2DWatchmen’, to simulate the whole protocol and test its robustness and real execution time, where the result shows good availability and effectiveness.

Many caching policies use machine learning to predict data reuse, but they ignore the impact of incorrect prediction on cache performance, especially for large-size objects. In this paper, we propose a smart segmented LRU (SS-LRU) replacement policy, which adopts a size-aware classifier designed for cache scenarios and considers the cache cost caused by misprediction. Besides, SS-LRU enhances the migration rules of segmented LRU (SLRU) and implements a smart caching with unequal priorities and segment sizes based on prediction and multiple access patterns. We conducted Extensive experiments under the real-world workloads to demonstrate the superiority of our approach over state-of-the-art caching policies.

Device-to-device (D2D) communication as direct communication technology has many application scenarios and plays a very important role in the fifth-generation (5G) era. Using D2D communication in third generation partnership project (3GPP) 5G Heterogeneous Network (HetNet) can effectively relieve the network traffic pressure and reduce the energy consumption of the base station. However, there are numerous security threats in D2D applications since the D2D communication remains in the early stage. The existing standards and solutions rarely consider device discovery, efficient authentication, mutual authentication, and key negotiation with privacy protection for D2D user equipment (UE) in heterogeneous access scenarios. In this article, we present a unified efficient anonymity proximity device discovery and batch authentication mechanism for heterogeneous D2D UEs based on a new proposed efficient pairing-free certificateless batch signature (CLBS), the identity-based prefix encryption and Chinese remainder theorem (CRT). Our proposed scheme can be applied to all the 5G heterogeneous access scenarios of D2D communication. The security analysis and performance results show that our scheme can achieve mutual authentication, key agreement, identity privacy protection, batch verification, and resist several protocol attacks with ideal efficiency.