| Presentation | 2019-11-15 Malicious URL Classification using Machine Learning Techniques Yu-Chen Chen, Li-Dong Chen, Yan-Ju Chen, Jiann-Liang Chen, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The Website security is an important research topic that must be pursued to protect internet users. Traditionally, blacklists of malicious websites are maintained, but they do not help in the detection of new malicious websites. This work proposes a machine learning architecture for detecting malicious URLs Forty-one features of malicious URLs are extracted using Domain, Alexa and Obfuscation Technique. ANOVA and XGBoost are used to identify the 17 most important features. Finally, dataset is used to train the XGBoost classifier, which has a classification accuracy of more than 99% and high efficiency. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Malicious URL / Obfuscation techniques / JavaScript detection / Artificial Intelligence / Feature selection |
| Paper # | IA2019-41 |
| Date of Issue | 2019-11-07 (IA) |
| Conference Information | |
| Committee | IA |
|---|---|
| Conference Date | 2019/11/14(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kwansei Gakuin University, Tokyo Marunouchi Campus (Sapia Tower) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | IA2019 - Workshop on Internet Architecture and Applications 2019 |
| Chair | Hiroyuki Osaki(Kwansei Gakuin Univ.) |
| Vice Chair | Rei Atarashi(IIJ) / Toru Kondo(Hiroshima Univ.) / Hiroshi Yamamoto(Ritsumeikan Univ.) |
| Secretary | Rei Atarashi(Kwansei Gakuin Univ.) / Toru Kondo(KDDI Research) / Hiroshi Yamamoto(NEC) |
| Assistant | Kenji Ohira(Osaka Univ.) / Daiki Nobayashi(Kyushu Inst. of Tech.) / Ryohei Banno(Tokyo Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Internet Architecture |
|---|---|
| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Malicious URL Classification using Machine Learning Techniques |
| Sub Title (in English) | |
| Keyword(1) | Malicious URL |
| Keyword(2) | Obfuscation techniques |
| Keyword(3) | JavaScript detection |
| Keyword(4) | Artificial Intelligence |
| Keyword(5) | Feature selection |
| 1st Author's Name | Yu-Chen Chen |
| 1st Author's Affiliation | National Taiwan University of Science and Technology(NTUST) |
| 2nd Author's Name | Li-Dong Chen |
| 2nd Author's Affiliation | National Taiwan University of Science and Technology(NTUST) |
| 3rd Author's Name | Yan-Ju Chen |
| 3rd Author's Affiliation | National Taiwan University of Science and Technology(NTUST) |
| 4th Author's Name | Jiann-Liang Chen |
| 4th Author's Affiliation | National Taiwan University of Science and Technology(NTUST) |
| Date | 2019-11-15 |
| Paper # | IA2019-41 |
| Volume (vol) | vol.119 |
| Number (no) | IA-291 |
| Page | pp.pp.79-83(IA), |
| #Pages | 5 |
| Date of Issue | 2019-11-07 (IA) |