PrivESD: A Privacy-Preserving Cloud-Edge Collaborative Logistic Regression Model Over Encrypted Streaming Data
inforesearchPeer-Reviewed
securityresearch
Source: IEEE Xplore (Security & AI Journals)October 6, 2025
Summary
PrivESD is a new system that allows machine learning classification (logistic regression, a technique for categorizing data) to work on encrypted streaming data (continuously flowing information that's been scrambled for privacy) while stored in the cloud. The system splits the computational work between cloud servers and edge devices (computers closer to where data originates) to reduce processing burden and privacy risks, and uses special encryption methods that still allow the system to compare values without revealing the actual data.
Classification
Attack SophisticationAdvanced
Impact (CIA+S)
confidentiality
AI Component TargetedTraining Data
Original source: http://ieeexplore.ieee.org/document/11192752
First tracked: February 12, 2026 at 02:22 PM
Classified by LLM (prompt v3) · confidence: 85%