A Lightweight Graph-based Method to Detect Pornographic and Gambling Websites with Imperfect Datasets

Ma, Xiaojun; Chen, Kewei; Zhao, Li; Yin, Jiangyi; Liu, Qingyun; Chen, Xunxun

doi:10.1109/trustcom56396.2022.00048

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2024

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Cited by 2 publications

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An Illegal Website Family Discovery Method Based on Association Graph Clustering

Xue,

Wen,

Wang

et al. 2024

Knowledge Science, Engineering and Management

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An Illegal Website Family Discovery Method Based on Association Graph Clustering

Xue,

Wen,

Wang

et al. 2024

Knowledge Science, Engineering and Management

View full text Add to dashboard Cite

MEDAL: A Multimodality-Based Effective Data Augmentation Framework for Illegal Website Identification

Wen,

Zhang,

Wang

et al. 2024

Electronics

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The emergence of illegal (gambling, pornography, and attraction) websites seriously threatens the security of society. Due to the concealment of illegal websites, it is difficult to obtain labeled data with high quantity. Meanwhile, most illegal websites usually disguise themselves to avoid detection; for example, some gambling websites may visually resemble gaming websites. However, existing methods ignore the means of camouflage in a single modality. To address the above problems, this paper proposes MEDAL, a multimodality-based effective data augmentation framework for illegal website identification. First, we established an illegal website identification framework based on tri-training that combines information from different modalities (including image, text, and HTML) while making full use of numerous unlabeled data. Then, we designed a multimodal mutual assistance module that is integrated with the tri-training framework to mitigate the introduction of error information resulting from an unbalanced single-modal classifier performance in the tri-training process. Finally, the experimental results on the self-developed dataset demonstrate the effectiveness of the proposed framework, performing well on accuracy, precision, recall, and F1 metrics.

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A Lightweight Graph-based Method to Detect Pornographic and Gambling Websites with Imperfect Datasets

Cited by 2 publications

References 13 publications

An Illegal Website Family Discovery Method Based on Association Graph Clustering

An Illegal Website Family Discovery Method Based on Association Graph Clustering

MEDAL: A Multimodality-Based Effective Data Augmentation Framework for Illegal Website Identification

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