Research on Deep Forgery Data Identification and Traceability Technology Based on Blockchain

With the acceleration of the digital transformation of the power system, the electronic data in the power production operation has shown an explosive growth. However, the increasing proliferation of deep forgery technology has brought huge hidden dangers to the electronic data management of power gr...

Full description

Saved in:
Bibliographic Details
Published in:2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA) pp. 230 - 234
Main Authors: Yang, Ke, Li, Da, Guo, Qinglei, Wang, Hejian, Bai, Desheng, Pan, Xiukui
Format: Conference Proceeding
Language:English
Published: IEEE 28.10.2022
Subjects:
blockchain
Cyberspace
data identification
Data science
data traceability
deep forgery
Digital transformation
forensic appraisal
Forensics
Forgery
Production
Watermarking
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the acceleration of the digital transformation of the power system, the electronic data in the power production operation has shown an explosive growth. However, the increasing proliferation of deep forgery technology has brought huge hidden dangers to the electronic data management of power grid enterprises, and it is urgent to build a trusted management system for electronic data. This paper proposes a blockchain-based deep forgery data identification and traceability framework. Firstly, a method of trusted identification of electronic data based on blockchain is proposed, which constructs the unique identification of data and embeds it in the electronic data as a digital watermark. Second, introduce blockchain-based electronic data forensic appraisal technology to conduct authenticity and similarity analysis of electronic data. Finally, a deep forgery data traceability mechanism based on digital identification is designed to realize deep forgery data traceability and dissemination supervision. After comparative analysis, the framework is more secure and efficient in deep forgery data supervision, and can provide key support for building a trusted content system in cyberspace.
DOI:10.1109/ICDSCA56264.2022.9988274