URL-based phishing detection using the entropy of non- A lphanumeric characters

Eint Sandi Aung, Hayato Yamana

研究成果: Conference contribution

抄録

Phishing is a type of personal information theft in which phishers lure users to steal sensitive information. Phishing detection mechanisms using various techniques have been developed. Our hypothesis is that phishers create fake websites with as little information as possible in a webpage, which makes it difficult for content- A nd visual similarity-based detections by analyzing the webpage content. To overcome this, we focus on the use of Uniform Resource Locators (URLs) to detect phishing. Since previous work extracts specific special-character features, we assume that non- A lphanumeric (NAN) character distributions highly impact the performance of URL-based detection. We hence propose a new feature called the entropy of NAN characters for URL-based phishing detection. Experimental evaluation with balanced and imbalanced datasets shows 96% ROC AUC on the balanced dataset and 89% ROC AUC on the imbalanced dataset, which increases the ROC AUC as 5 to 6% from without adopting our proposed feature.

本文言語English
ホスト出版物のタイトル21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Proceedings
編集者Maria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Anderst-Kotsis
出版社Association for Computing Machinery
ISBN(電子版)9781450371797
DOI
出版ステータスPublished - 2019 12 2
イベント21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Munich, Germany
継続期間: 2019 12 22019 12 4

出版物シリーズ

名前ACM International Conference Proceeding Series

Conference

Conference21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019
国/地域Germany
CityMunich
Period19/12/219/12/4

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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