DeZent: Decentralized z-Anonymity with Privacy-Preserving Coordination

• URL: http://arxiv.org/abs/2603.08854v1
• Date: Mon, 09 Mar 2026 19:14:23 GMT
• Title: DeZent: Decentralized z-Anonymity with Privacy-Preserving Coordination
• Abstract summary: Privacy-enhancing technologies like z-anonymity offer efficient anonymization for continuous data streams.<n>We introduce deZent, a decentralized implementation of z-anonymity that minimizes trust in the central entity.<n>Our results show that deZent achieves comparable performance to centralized z-anonymity in terms of publication ratio.
• Score: 2.0625936401496237
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Analyzing large volumes of sensor network data, such as electricity consumption measurements from smart meters, is essential for modern applications but raises significant privacy concerns. Privacy-enhancing technologies like z-anonymity offer efficient anonymization for continuous data streams by suppressing rare values that could lead to re-identification, making it particularly suited for resource-constrained environments. Originally designed for centralized architectures, z-anonymity assumes a trusted central entity. In this paper, we introduce deZent, a decentralized implementation of z-anonymity that minimizes trust in the central entity by realizing local z-anonymity with lightweight coordination. We develop deZent using a stochastic counting structure and secure sum to coordinate private anonymization across the network. Our results show that deZent achieves comparable performance to centralized z-anonymity in terms of publication ratio, while reducing the communication overhead towards the central entity. Thus, deZent presents a promising approach for enhancing privacy in sensor networks while preserving system efficiency.

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