Edge Video Stream Encoding with Confidential Content Encryption
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Solution Overview
Problem
The increasing number of Internet of Things (IoT) devices and mobile devices using cloud services leads to exponential network requirements, resulting in increased latency and higher bandwidth costs, which edge computing struggles to accommodate, especially when processing video streams for applications like computer vision that require deep learning tasks.
Innovation Solution
An edge device partitions video stream image content into confidential and non-confidential parts, encrypts the confidential part, and encodes both parts into an encoded video stream for secure transmission to processing servers, using a confidentiality-enforced autoencoder framework to optimize video transmission and protect sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all video stream data is transmitted to cloud servers for processing, then deep learning tasks can be performed, but network bandwidth consumption and latency increase significantly
Solution Approach 1:
The video stream is segmented into confidential and non-confidential parts at the edge device. Non-confidential parts are transmitted to cloud servers for deep learning processing, while confidential parts are encrypted and kept locally. This segmentation allows selective transmission of only necessary data, reducing bandwidth consumption while maintaining processing capability for non-sensitive content.
2Reliability
If video streams are encrypted for security, then confidential content is protected, but transmission efficiency and processing speed may be reduced
Solution Approach 1:
Different security measures are applied to different parts of the video stream based on their confidentiality requirements. Confidential parts are encrypted with high security measures, while non-confidential parts are transmitted without encryption or with lighter security measures. This local differentiation of security quality optimizes the balance between security and transmission efficiency.
3Loss of time
If edge devices process video streams locally, then latency is reduced, but devices with varying security levels may not receive appropriate protection
Solution Approach 1:
The security protocol is made dynamic by allowing edge devices to adaptively encrypt only the confidential portions of video streams based on their local security capabilities and requirements. This dynamic approach enables devices with different security levels to operate efficiently while maintaining appropriate protection for sensitive content, rather than applying uniform encryption to all devices.
Data Source
AI summary
Edge device video processing with encryption of confidential image content is provided. The process includes obtaining, by the edge device, a video stream, and partitioning image content of the video stream into a confidential part and a non-confidential part. Further, the process includes encrypting, by the edge device, the confidential part of the image content to obtain encrypted image content from the confidential part and non-encrypted image content from the non-confidential part of the image content. In addition, the process includes encoding, by the edge device, the encrypted image content and the non-encrypted image content into an encoded video stream, and transmitting the encoded video stream to one or more processing servers.