HinPage: illegal and harmful webpage identification using transductive classification. (English) Zbl 07730531
Deng, Yi (ed.) et al., Information security and cryptology. 18th International conference, Inscrypt 2022, Beijing, China, December 11–13, 2022. Revised selected papers. Cham: Springer. Lect. Notes Comput. Sci. 13837, 373-390 (2023).
Summary: With the growing popularity of the Internet, websites could make significant profit by hosting illegal and harmful content, such as violence, sexual, illegal gambling, drug abuse, etc. They are serious threats to a safe and secure Internet, and they are especially harmful to the underage population. Government agencies, ISPs, network administrators at various levels, and parents have been seeking for accurate and robust solutions to block such illegal and harmful webpages. Existing solutions detect inappropriate pages based on content, e.g., using keyword matching or content-based image classification. They could be easily escaped by altering the internal format of texts or images, e.g., mixing different alphabets. In this paper, we propose to utilize relatively stable features extracted from the relationships between the targeted illegal/harmful webpages to discover and identify illegal webpages. We introduce a new mechanism, namely HinPage, that utilizes such features for the robust identification of PG (pornographic and gambling) pages. HinPage models the candidate PG pages and the resources on the pages with a heterogeneous information network (HIN). A transductive classification algorithm is then applied to the HIN to identify PG pages.
Through experiments on 10,033 candidate PG pages, we demonstrate that HinPage achieves an accuracy of 83.5% on PG page identification. In particular, it is able to identify illegal/harmful PG pages that cannot be recognized by SOTA commercial products.
For the entire collection see [Zbl 1517.94007].
Through experiments on 10,033 candidate PG pages, we demonstrate that HinPage achieves an accuracy of 83.5% on PG page identification. In particular, it is able to identify illegal/harmful PG pages that cannot be recognized by SOTA commercial products.
For the entire collection see [Zbl 1517.94007].
MSC:
| 68M11 | Internet topics |
Keywords:
illegal and harmful webpages; webpage classification; heterogeneous information network; transductive classificationSoftware:
metapath2vecReferences:
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