Research on Key Technologies of an Intelligent Judgment and Homologous Expansion System for Fraud-Related Risk URLs

DOI

10.2991/978-94-6239-766-8_2How to use a DOI?

Keywords

Fraud-related URL; fraud-related APK; intelligent judgment; homologous expansion; feature gene; dynamic-static analysis; whole-network mining

Abstract

In response to the technical countermeasures in current telecommunications network fraud, such as template-based generation of fraudulent APKs and URLs, code obfuscation and reinforcement, rapid domain name rotation, and dynamic hiding of behaviors, traditional single-dimension detection and manual analysis methods can no longer meet practical needs. This paper presents the design and implementation of an intelligent assessment and homologous expansion system for fraud-related risk URLs. The system integrates three core technologies: dynamic and static APK detection and analysis, multi-dimensional URL feature extraction, and global homologous. By employing automated unpacking, sandbox behavior simulation, and anti-detection hooks, it overcomes APK reinforcement and feature hiding to accurately extract associated URLs. A 14-dimensional URL feature system is constructed and a unique feature gene is generated for precise characterization of fraud-related URLs. Based on feature genes and the DBSCAN clustering algorithm, the system achieves dynamic mining and expansion of globally homologous fraud-related URLs.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Hang Du
AU  - Menglei Li
PY  - 2026
DA  - 2026/09/04
TI  - Research on Key Technologies of an Intelligent Judgment and Homologous Expansion System for Fraud-Related Risk URLs
BT  - Proceedings of the 2026 6th International Conference on Education, Information Management and Service Science  (EIMSS 2026)
PB  - Atlantis Press
SP  - 4
EP  - 12
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6239-766-8_2
DO  - 10.2991/978-94-6239-766-8_2
ID  - Du2026
ER  -