Racing Drone Goggles Data Security via Frame Segmentation
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Solution Overview
Problem
Existing racing drone goggles lack effective protection for real-time image transmission streams, as they are vulnerable to interception and decoding by other devices due to the public SD protocol used by SD cards, leading to potential data leakage and security issues during live broadcasts.
Innovation Solution
The implementation of a data processing method and device that utilizes two storage devices within the goggles, where image frames are classified and stored differently, with critical frames stored internally and less critical frames stored on an SD card, disrupting the time sequence and preventing complete data interception, thereby enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time image transmission data is continuously written to SD card at constant speed, then data storage is simple and continuous, but the data can be intercepted and decoded by other devices compatible with SD protocol, compromising security
Solution Approach 1:
The patent divides the continuous image transmission data stream into discrete image frames and further segments them into two types: key frames and non-key frames. This segmentation is implemented by separating the storage locations - key frames are stored in the first storage device (internal memory) while non-key frames are stored in the second storage device (SD card). This segmentation prevents complete data interception because an attacker would need to intercept both storage devices simultaneously to reconstruct the full video stream, thus resolving the contradiction between data security and storage simplicity.
2Reliability
If all image frames are stored in the same storage device, then storage management is simple, but intercepted data can be fully decoded, leading to data leakage
Solution Approach 1:
The patent applies local quality by assigning different storage characteristics to different types of image frames. Specifically, key frames (which contain essential image information for video reconstruction) are stored in the first storage device with higher security characteristics, while non-key frames are stored in the second storage device (SD card) with easier access characteristics. This differentiated storage approach ensures that even if the SD card is accessed by unauthorized devices, the critical key frames remain protected, thus achieving data protection while maintaining manageable storage complexity through clear classification rules.
3Reliability
If image frames are classified and stored in different storage devices, then data interception is disrupted and security is enhanced, but storage system complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-classifying image frames into key frames and non-key frames before storage, and pre-assigning them to different storage devices based on their type. This classification and assignment is done in advance according to predetermined criteria (such as frame type identification), so that when data interception attempts occur, the security architecture is already in place. This preliminary organization reduces the operational complexity during runtime, as the system follows pre-established storage rules rather than making complex real-time decisions, thus resolving the contradiction between enhanced security and system complexity.
Data Source
AI summary
An embodiment of the present disclosure provides a data processing method, a device, and a pair of racing drone goggles. The method includes receiving image transmission data; determining a current image frame of the image transmission data; and storing images frames determined as a first type in a first storage device, and storing the images frames determined as a second type in a second storage device. By classifying and storing the image transmission data, the image transmission data can be protected from other terminal devices, and the data security is improved.