This letter presents ZIP (zero-effort ZIgBee Proximity detection), a novel technique to detect the proximity of two Internet-of-Things devices. Based on the ZigBee technology, ZIP embodies the first zero-effort solution by differing from existing ones that resort to the use of tailor-made hardware, multiple antenna installments, the employment of a third-party device, or user involvement. At the heart of ZIP is the construction of a feature-designated decision tree built on received signal strength. An ensemble prediction method is further designed to aggregate the outputs of multiple decision trees for detection accuracy improvement. Practical experiments are conducted to show the reliability and robustness of ZIP.

Public key encryption with keyword search (PEKS) enables users to search over encrypted data outsourced to an untrusted server. Unfortunately, updates to the outsourced data may incur information leakage by exploiting the previously submitted queries. Prior works addressed this issue by means of forward privacy, but most of them suffer from significant performance degradation. In this paper, we present a novel forward private PEKS scheme leveraging Software Guard Extension (SGX), a trusted execution environment provided by Intel. The proposed scheme presents substantial performance improvements over prior work. Specifically, we reduce the query processing cost from $O\left(n\right)$ to $O\left(1\right)$, where n is the number of encrypted data. According to our performance analysis, the overall computation time is reduced by 80% on average. Lastly, we provide a formal security definition of SGX-based forward private PEKS, as well as a rigorous security proof of the proposed scheme.