Synergistic Commutative Algorithm for Securing Vector Spatial Data via GD‐PBIBD Fingerprint Encoding and Data Encryption.

ABSTRACT As a fundamental component that supports business connectivity and enables intelligent decision‐making, vector spatial data encounter increasing copyright and security challenges throughout their lifecycle. There is an imminent need for a comprehensive lifecycle protection solution to ensure data security and adherence to copyright laws. This study introduces an integrated protection scheme designed to address copyright and security issues across the entire lifecycle of vector spatial data. First, DNA encryption is applied to the vector spatial data, with the key subsequently encrypted using the RSA public key. Concurrently, GD‐PBIBD fingerprint encoding is used to generate a fingerprint sequence. Thereafter, this sequence is scrambled using logistic mapping, and a quantization mechanism embeds the scrambled fingerprint sequence into the coordinates. Subsequently, the RSA private key is used to decrypt the key and extract the fingerprint information. Finally, logistic mapping is employed to restore the fingerprint sequence, and Hamming distance calculations are used to identify colluding users and trace potential data leaks. Experimental studies indicate that the proposed DNA encryption algorithm is effective for various types of vector spatial data, including point, polyline, and polygon data. It features a large key space and high key sensitivity. Furthermore, the GD‐PBIBD fingerprint encoding is simple to construct, offers excellent imperceptibility, and provides robust resistance to both single‐ and multi‐user attacks. This research addresses the gap in full lifecycle copyright and security protection for vector spatial data and offers a holistic solution for secure data circulation, thereby demonstrating significant practical value. [ABSTRACT FROM AUTHOR]