Yingying Huangfu | Searcharxiv

arXiv2026

On the Leaky Private Information Retrieval with Side Information

This paper investigates the problem of Leaky Private Information Retrieval with Side Information (L-PIR-SI), providing a fundamental characterization of the trade-off among leaky privacy, side information, and download cost. We propose a unified probabilistic framework to design L-PIR-SI schemes under $\varepsilon$-differential privacy variants of both $W$-privacy and $(W, S)$-privacy. Explicit upper bounds on the download cost are derived, which strictly generalize existing results: our bounds recover the capacity of perfect PIR-SI as $\varepsilon \to 0$, and reduce to the known $\varepsilon$-leaky PIR rate in the absence of side information. Furthermore, we conduct a refined analysis of the privacy--utility trade-off at the scaling-law level, demonstrating that the leakage ratio exponent scales as $\mathcal{O}(\log \frac{K}{M + 1})$ under leaky $W$-privacy, and as $\mathcal{O}(\log K)$ under leaky $(W, S)$-privacy in the minimal non-trivial setting $M = 1$, where $K$ and $M$ denote the number of messages and the side information size, respectively.

cs.IT↗

arXiv2025

A Cooperative Statistical Approach for Abnormal Node Detection with Adversary Resistance

Distinguishing abnormal nodes from those with normal packet loss in clusters helps reduce the loss of clustered network resources. The detection performance of existing detection schemes is limited by the techniques to quantify node behaviors, and most schemes cannot avoid being misled by the falsified information. This paper presents a novel probabilistic abnormal node detection scheme CSD -- Cooperative Statistical Detection -- for accurate and efficient detection in the existence of falsified detection data in clustered networks. Specifically, employing the likelihood ratio test (LRT) based detection method to measure node forwarding behaviors, we propose a modified Z-score based falsification-resistant mechanism to filter out falsifications. We show that both the false alarm and missed detection probabilities can decrease exponentially if and only if the transmissions from the nodes falsifying the data are less than half of the total. Furthermore, the optimal threshold of the modified Z-score method is derived, which guarantees perfect detection of our CSD under any falsification strategy in the proposed detection model. Evaluation results validate the effectiveness, robustness, and superiority of our scheme compared to the state-of-the-art.

eess.SY↗