English

A Path to Holistic Privacy in Stream Processing Systems

Cryptography and Security 2023-05-22 v1 Machine Learning

Abstract

The massive streams of Internet of Things (IoT) data require a timely analysis to retain data usefulness. Stream processing systems (SPSs) enable this task, deriving knowledge from the IoT data in real-time. Such real-time analytics benefits many applications but can also be used to violate user privacy, as the IoT data collected from users or their vicinity is inherently sensitive. In this paper, we present our systematic look into privacy issues arising from the intersection of SPSs and IoT, identifying key research challenges towards achieving holistic privacy protection in SPSs and proposing the solutions.

Keywords

Cite

@article{arxiv.2305.11638,
  title  = {A Path to Holistic Privacy in Stream Processing Systems},
  author = {Mikhail Fomichev},
  journal= {arXiv preprint arXiv:2305.11638},
  year   = {2023}
}

Comments

Extended Abstract accepted to MobiSys 2023

R2 v1 2026-06-28T10:39:12.071Z