Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 523-530.doi: 10.11896/jsjkx.210300083

• Information Security • Previous Articles     Next Articles

Study on Automatic Synthetic News Detection Method Complying with Regulatory Compliance

MAO Dian-hui1,2, HUANG Hui-yu1, ZHAO Shuang1   

  1. 1 Beijing Key Laboratory of Big Data Technology for Food Safety,Beijing Technology and Business University,Beijing 100048,China
    2 National Engineering Laboratory for Agri-product Quality Traceability,BeijingTechnology and Business University,Beijing 100048,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:MAO Dian-hui,born in 1979,professor.His main research interests include integration of blockchain and AI.
  • Supported by:
    National Social Science Fundation of China(18BGL202).

Abstract: Automatic Synthetic news has been widely used in formatted news information such as financial market analysis and event reports,which has great social impact.However,when centralized storage is adopted for regulatory,it is easy for regulators or third parties to steal and tamper with the information.Therefore,under the premise of ensuring detection efficiency and accur-acy,it is particularly important to protect private information from being leaked.In this paper,an automaticsynthetic news detection method is proposed,which meets the requirements of regulations.The goal is to record data activities in distributed ledger while ensuring that only regulatory agencies can process news information by data access token.This method designs two types of distributed ledgers and calls them through intelligent contracts to realize authorization mechanism and log recording.Only honest participation can be recognized by the blockchain and prove compliance with regulation.Furthermore,the method endows edge nodes with computing power by adopting lightweight detection algorithms IDF-FastText,prevents the proliferation of various synthetic news from the source,and realizes the timeliness of regulation.The GPT-2 detection algorithm based on general adversarial networks(GAN) is deployed on the server for the regulator to verify the detection results.Finally,the feasibility of the proposed design concept is proved by experiments.

Key words: Blockchain, Data protection, Deep learning, News detection

CLC Number: 

  • TP391.9
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