Invisible Character Watermarking for HD Map Data Integrity
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Solution Overview
Problem
Existing watermark algorithms for high-definition maps in the OpenDrive format lack robustness and are not suitable for adjusting document structures, and existing algorithms based on XML file characteristics do not adequately address the security and confidentiality needs of high-definition map data.
Innovation Solution
A digital watermarking method using invisible characters and logistic maps to scramble identifiers and attribute values, embedding watermark information in a way that maintains data availability and accuracy, combined with Hamming code technology for error correction and resistance to attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing watermark algorithms based on document structures (ZIP, Word, PDF) are used, then watermark embedding is achieved, but the algorithms are not suitable for OpenDrive format data which does not support document structure adjustments
Solution Approach 1:
The patent changes the watermark embedding approach from document structure manipulation to inserting invisible characters (specific Unicode characters like U+200B, U+200C, U+200D) within existing data fields. This parameter change allows watermarking of OpenDrive files without requiring structural modifications, thus resolving the contradiction between embedding reliability and format adaptability
Solution Approach 2:
The patent introduces invisible characters as intermediaries between the watermark data and the OpenDrive file content. These invisible characters serve as carriers that embed watermark information without disrupting the file's native structure or requiring format-specific adjustments, enabling universal applicability across different OpenDrive versions
2Reliability
If watermark algorithms based on XML file characteristics are used, then watermark embedding is achieved, but the algorithms do not adequately address the security and confidentiality needs of high-definition map data
Solution Approach 1:
The patent applies preliminary scrambling to the watermark sequence using logistic maps before embedding. This preliminary action ensures that even if the watermark is extracted, the original information remains encrypted and unintelligible without the scrambling key, thereby addressing security concerns while maintaining embedding functionality
Solution Approach 2:
The patent combines multiple protection mechanisms: invisible character embedding, logistic map scrambling, and Hamming code error correction. This composite approach creates a multi-layered security system that simultaneously achieves reliable watermark embedding and enhanced data security, countering the harmful factor of insufficient confidentiality protection
3Ease of manufacture
If invisible character encoding is used for watermark embedding, then watermark embedding is achieved, but the robustness is poor and watermarks are easily removed
Solution Approach 1:
The patent incorporates Hamming code error correction before embedding the watermark. This beforehand cushioning provides error detection and correction capabilities that protect the watermark against removal attempts, transmission errors, and data modifications, significantly enhancing robustness while maintaining the simplicity of invisible character embedding
Solution Approach 2:
The patent applies logistic map scrambling to the watermark sequence before embedding. This preliminary action encrypts the watermark information, making it resistant to removal and extraction attacks. The combination of scrambling and error correction codes creates a robust watermarking system that maintains ease of implementation
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively embeds and detects watermarks in high-definition maps without altering data availability, ensuring high accuracy and robustness against translation, rotation, scaling, and clipping attacks.
Implementation Method 1
scrambling an embedding sequence of watermark information based on a logistic map to generate a chaotic sequence, the logistic map being expressed as follows: Xn+1=f(Xn,μ)=μXn(1−Xn)
Implementation Method 2
converting the initial condition X0 of the logistic map into an invisible character according to a mapping relationship between decimal characters and invisible characters
Implementation Method 3
combined with Hamming code technology for error correction and resistance to attacks
Data Source
AI summary
A watermarking method for a high-definition map based on invisible characters includes: firstly, establishing mapping relations between invisible characters and bit characters, a space character, and decimal digits; and combining watermark characters with corresponding positions thereof, adding Hamming code into a watermark character sequence, and converting the watermark character sequence into invisible characters to construct a composite watermark character sequence. Before watermark detection, a sequence of elements in map data is scrambled according to logistic chaotic mapping, and then the composite watermark character sequence is embedded according to the scrambled sequence. During watermark detection, the data are preprocessed, a sequence during watermark embedding is obtained, and then watermark information is extracted, errors are corrected, and an error correcting code is removed after correction to obtain final watermark information. According to the watermarking method, watermark embedding and watermark detection can be realized not changing data availability and high-accuracy characteristic.