Sequential Change Detection for Multiple Data Streams with Differential Privacy

Mathematics > Statistics Theory [Submitted on 14 Apr 2026] Sequential Change Detection for Multiple Data Streams with Differential Privacy Lixing Zhang, Liyan Xie, Ruizhi Zhang Sequential change-point detection seeks to rapidly identify distributional changes in streaming data while controlling false alarms. Existing multi-stream detection methods typically rely on non-private access to raw observations or intermediate statistics, limiting their usage in privacy-sensitive settings. We study sequential change-point detection for multiple data streams under differential privacy constraints. We consider multiple independent streams undergoing a synchronized change at an unknown time and in an unknown subset of streams, and propose DP-SUM-CUSUM, a differentially private detection procedure based on the summation of per-stream CUSUM statistics with calibrated Laplace noise injection. We show that DP-SUM-CUSUM satisfies sequential \varepsilon-differential privacy and derive bounds on the average run length to false alarm and the worst-case average detection delay, explicitly characterizing the privacy--efficiency tradeoff. A truncation-based extension is also presented to handle distributional shifts with unbounded log-likelihood ratios. Simulations and experiments on an Internet of Things (IoT) botnet dataset validate the proposed approach. Comments: Accepted to the 2026 IEEE International Symposium on Information Theory (ISIT 2026) Subjects: Statistics Theory (math.ST); Cryptography and Security (cs.CR) Cite as: arXiv:2604.13274 [math.ST]   (or arXiv:2604.13274v1 [math.ST] for this version)   https://doi.org/10.48550/arXiv.2604.13274 Focus to learn more Submission history From: Lixing Zhang [view email] [v1] Tue, 14 Apr 2026 20:08:07 UTC (588 KB) Access Paper: HTML (experimental) view license Current browse context: math.ST < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.CR math stat stat.TH References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)