Video Evidence Authentication via Cryptographic Hashing
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Solution Overview
Problem
Digital video evidence can be easily altered or tampered with, leading to challenges in its authenticity and admissibility in legal or official settings, and existing video recording systems have limited fields of view and are prone to damage or inoperability during critical events.
Innovation Solution
A digital media management and evidence report generating system that includes cameras, local and remote memory, encryption, and authentication methods to verify the integrity of video footage, allowing for the creation of an evidence package with authentication identifiers and supporting information to ensure the video's authenticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital video evidence is used to capture events, then the ability to record and present evidence is improved, but the video can be easily altered or tampered with, compromising its authenticity
Solution Approach 1:
The system performs preliminary authentication by generating cryptographic hash values of the video data at the time of recording and storing these hash values along with metadata. This preliminary action creates a digital fingerprint that can be used to verify the video's integrity later, preventing tampering before the verification step occurs.
Solution Approach 2:
The system implements a feedback mechanism where the authentication result (whether the video matches its original hash) is fed back to the user interface. This feedback allows users to immediately see whether the video evidence has been tampered with, enabling real-time verification and building trust in the evidence presentation process.
2Adaptability or versatility
If a single car-mounted camera is used to record events, then the device complexity is reduced, but the field of view is limited and the camera may become damaged or inoperative during critical events
Solution Approach 1:
The system merges video data from multiple sources including front-facing cameras, rear-facing cameras, and side-mounted cameras into a single comprehensive evidence package. By combining these multiple camera feeds and synchronizing them temporally and spatially, the system achieves comprehensive coverage without requiring a single complex camera system.
Solution Approach 2:
The evidence package system is designed to be universal and multi-functional, accepting video input from various camera types and configurations (single camera, multiple cameras, different mounting positions). This universal approach allows the same system to handle diverse recording scenarios while maintaining consistent authentication and presentation capabilities.
3Loss of information
If video metadata is included to provide additional information, then the evidentiary value is improved, but the metadata accuracy may be unverifiable, affecting the integrity of the whole video
Solution Approach 1:
The system performs preliminary hashing of the metadata along with the video data, creating a combined digital fingerprint. This preliminary action ensures that any alteration to the metadata will be detected during verification, making the metadata as reliable as the video content itself.
Solution Approach 2:
Cryptographic hash functions serve as intermediaries between the video content and the verification process. These hash values act as mediators that confirm the integrity of both video and metadata without requiring direct verification of the metadata content itself, thus maintaining reliability while preserving information completeness.
Data Source
AI summary
A method for automatically authenticating unknown video data based on known video data stored at a client server is provided, wherein, unknown and known video data each are made up of segments and include metadata, a hash message digest, and a serial code. The method involves selecting a first segment of the unknown video and locating the serial code within the first segment of the unknown video data. The serial code is used to locate a corresponding first segment in the known video data. The first segment may include a known hash message digest. A new hash message digest for the first segment of the unknown video data is generated and compared with the known hash message digest. If they match, the segment of unknown video data is authentic.