ANTON Framework Based on Semantic Focused Crawler to Support Web Crime Mining Using SVM

  • Javad Hosseinkhani
  • Hamed TaherdoostEmail author
  • Solmaz Keikhaee


Crime analysis is one of the important activities in information security agencies. They collect the crimes data with appropriate procedures and tools from the Web. The main challenge which many of these agencies are facing is to have an efficient and accurate analysis of the increasing rate of crime information. The cybercrime information presented on Web pages are in the form of text and need to be analyzed and investigated. Although some approaches have been presented to support Web crime mining, the issues of efficiency and effectiveness still exist. Due to the fact that most of the crime information is based on Web ontology, semantic technology can be used to study the patterns and the process of Web crimes. Therefore, in order to extract and reveal the Internet crime, an improved Web ontology is useful to extract the characteristics and relationships among Web pages for the recreation and extraction of crime scenarios. The main purpose of this study is to develop an optimized ontology-based approach for Web crime mining. The proposed framework was designed based on enhanced crime ontology using ant-miner focused crawler, which drew inspiration from biological researches on the ant foraging behavior. Ant-colony optimization was used to optimize the proposed framework. The proposed work was evaluated based on accuracy criteria. The evaluation results show that this research provides an effective solution through crime ontologies and an enhanced ant-based crawler.


ANTON framework Semantic focused crawler Web crime mining Naïve/Bayes SVM 



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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer, Damavand BranchIslamic Azad UniversityDamavandIran
  2. 2.Research Club, Research and Development DepartmentHamta GroupKuala LumpurMalaysia
  3. 3.Hamta Academy, Advanced Academic and Industrial Training CentreKuala LumpurMalaysia
  4. 4.Tablokar Co, Switchgear ManufacturerTehranIran

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