Netinfo Security ›› 2023, Vol. 23 ›› Issue (10): 77-82.doi: 10.3969/j.issn.1671-1122.2023.10.011

Previous Articles     Next Articles

Detection and Identification Model of Gambling Websites Based on Multi-Modal Data

ZHAO Xinhe1,2, XIE Yongheng3,4(), WAN Yueliang3,4, WANG Jinmiao3,4   

  1. 1. School of Information Networking Security, People’s Public Security University of China, Beijing 100038, China
    2. Zhoucun Branch, Zibo City Public Security Bureau, Zibo 255300, China
    3. The Third Research Institute of Ministry of Public Security, Shanghai 200031, China
    4. Run Technologies Co., Ltd. Beijing,Beijing 100192, China
  • Received:2023-06-26 Online:2023-10-10 Published:2023-10-11

Abstract:

This paper proposed a gambling website detection and recognition model based on multimodal data. Firstly, it constructed a Bert feature extraction model based on text features and a VGG19 feature extraction model based on image features; secondly, the method improved the classification effect of gambling website detection and recognition based on feature fusion and changing the loss function; lastly, this paper validated the method on self-constructed positive and negative samples of 1:5, 1:10, and 1:20 datasets. The experimental results indicate that the more obvious the imbalance of positive and negative samples is, the more obvious the advantage of the proposed method is, and it can detect and recognise gambling websites well.

Key words: multi-modal, gambling website, feature extraction

CLC Number: