Vehicle cockpit data leakage prevention methods, devices, equipment and storage media
By encrypting vehicle cockpit data and performing vector dimension compression and noise processing in a trusted execution environment, ultra-low-dimensional feature vectors are generated, solving the leakage and reverse inference problems during data transmission and achieving secure data transmission and privacy protection.
CN122316741APending Publication Date: 2026-06-30HEXINLI INTELLIGENT CONTROL TECHNOLOGY (SHANGHAI) CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HEXINLI INTELLIGENT CONTROL TECHNOLOGY (SHANGHAI) CO LTD
- Filing Date
- 2026-04-09
- Publication Date
- 2026-06-30
AI Technical Summary
Technical Problem
Vehicle cockpit data is easily intercepted and misused during transmission, and anonymized data is easily reverse-engineered by attackers, resulting in a high risk of leakage.
Method used
Vehicle cockpit data is encrypted, transmitted to a trusted execution environment via a secure bus, and then compressed into vector dimensions and combined with a random noise array to generate ultra-low-dimensional feature vectors and semantic abstraction results.
Benefits of technology
It effectively prevents data leakage during transmission, reduces the risk of reverse engineering, and enhances transmission security and data privacy protection.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122316741A_ABST
Abstract
This application relates to the field of vehicle data security technology, and in particular to a method, apparatus, device, and storage medium for preventing vehicle cockpit data leakage. The method includes: encrypting vehicle cockpit data to obtain encrypted cockpit data; transmitting the encrypted cockpit data to a trusted execution environment based on a preset secure bus; compressing the encrypted cockpit data in the trusted execution environment to obtain an ultra-low-dimensional feature vector; and obtaining a semantic abstraction result based on the ultra-low-dimensional feature vector and a random noise array. This application effectively improves the transmission security of vehicle cockpit data and effectively reduces the risk of vehicle cockpit data leakage.
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