$α$-leakage Interpretation of Rényi Capacity

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Ding, Ni, Farokhi, Farhad, Guo, Tao, Xu, Yinfei, Zhang, Xiang
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915538787106816
author Ding, Ni
Farokhi, Farhad
Guo, Tao
Xu, Yinfei
Zhang, Xiang
author_facet Ding, Ni
Farokhi, Farhad
Guo, Tao
Xu, Yinfei
Zhang, Xiang
contents For $\tilde{f}(t) = \exp(\frac{α-1}αt)$, this paper shows that the Sibson mutual information is an $α$-leakage averaged over the adversary's $\tilde{f}$-mean relative information gain (on the secret) at elementary event of channel output $Y$ as well as the joint occurrence of elementary channel input $X$ and output $Y$. This interpretation is used to derive a sufficient condition that achieves a $δ$-approximation of $ε$-upper bounded $α$-leakage. A $Y$-elementary $α$-leakage is proposed, extending the existing pointwise maximal leakage to the overall Rényi order range $α\in [0,\infty)$. Maximizing this $Y$-elementary leakage over all attributes $U$ of channel input $X$ gives the Rényi divergence. Further, the Rényi capacity is interpreted as the maximal $\tilde{f}$-mean information leakage over both the adversary's malicious inference decision and the channel input $X$ (represents the adversary's prior belief). This suggests an alternating max-max implementation of the existing generalized Blahut-Arimoto method.
format Preprint
id arxiv_https___arxiv_org_abs_2510_06622
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle $α$-leakage Interpretation of Rényi Capacity
Ding, Ni
Farokhi, Farhad
Guo, Tao
Xu, Yinfei
Zhang, Xiang
Information Theory
For $\tilde{f}(t) = \exp(\frac{α-1}αt)$, this paper shows that the Sibson mutual information is an $α$-leakage averaged over the adversary's $\tilde{f}$-mean relative information gain (on the secret) at elementary event of channel output $Y$ as well as the joint occurrence of elementary channel input $X$ and output $Y$. This interpretation is used to derive a sufficient condition that achieves a $δ$-approximation of $ε$-upper bounded $α$-leakage. A $Y$-elementary $α$-leakage is proposed, extending the existing pointwise maximal leakage to the overall Rényi order range $α\in [0,\infty)$. Maximizing this $Y$-elementary leakage over all attributes $U$ of channel input $X$ gives the Rényi divergence. Further, the Rényi capacity is interpreted as the maximal $\tilde{f}$-mean information leakage over both the adversary's malicious inference decision and the channel input $X$ (represents the adversary's prior belief). This suggests an alternating max-max implementation of the existing generalized Blahut-Arimoto method.
title $α$-leakage Interpretation of Rényi Capacity
topic Information Theory
url https://arxiv.org/abs/2510.06622