A genetic algorithm based model for chinese phishing E-commerce websites detection

Zhijun Yan; Su Liu; Hansi Jiang; Hangzhou Yang; Tianmei Wang; Baowen Sun

doi:10.1007/978-3-319-39396-4_25

A genetic algorithm based model for chinese phishing E-commerce websites detection

Zhijun Yan^*, Su Liu, Hansi Jiang, Hangzhou Yang, Tianmei Wang, Baowen Sun

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

We propose a new Chinese phishing e-commerce websites detection model which integrates the URL features and web features of websites. Some unique features of Chinese e-Commerce websites are included and Sequential Minimal Optimization (SMO) algorithm is applied to identify the phishing ecommerce websites. At the same time, we adopt the genetic algorithm (GA) to optimize the detection model. The evaluation results show that the performance of SMO algorithm is better than the baseline model and GA improves the detection accuracy significantly.

Original language	English
Title of host publication	HCI in Business, Government, and Organizations
Subtitle of host publication	eCommerce and Innovation - 3rd International Conference, HCIBGO 2016 and Held as Part of HCI International 2016, Proceedings
Editors	Fiona Fui-Hoon Nah, Chuan-Hoo Tan
Publisher	Springer Verlag
Pages	270-279
Number of pages	10
ISBN (Print)	9783319393957
DOIs	https://doi.org/10.1007/978-3-319-39396-4_25
Publication status	Published - 2016
Event	3rd International Conference on HCI in Business, Government, and Organizations: eCommerce and Innovation, HCIBGO 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 - Toronto, Canada Duration: 17 Jul 2016 → 22 Jul 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9751
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on HCI in Business, Government, and Organizations: eCommerce and Innovation, HCIBGO 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016
Country/Territory	Canada
City	Toronto
Period	17/07/16 → 22/07/16

Keywords

Chinese phishing website detection
E-commerce
Genetic algorithm
Sequential minimal optimization

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10.1007/978-3-319-39396-4_25

Cite this

Yan, Z., Liu, S., Jiang, H., Yang, H., Wang, T., & Sun, B. (2016). A genetic algorithm based model for chinese phishing E-commerce websites detection. In F. F.-H. Nah, & C.-H. Tan (Eds.), HCI in Business, Government, and Organizations: eCommerce and Innovation - 3rd International Conference, HCIBGO 2016 and Held as Part of HCI International 2016, Proceedings (pp. 270-279). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9751). Springer Verlag. https://doi.org/10.1007/978-3-319-39396-4_25

Yan, Zhijun ; Liu, Su ; Jiang, Hansi et al. / A genetic algorithm based model for chinese phishing E-commerce websites detection. HCI in Business, Government, and Organizations: eCommerce and Innovation - 3rd International Conference, HCIBGO 2016 and Held as Part of HCI International 2016, Proceedings. editor / Fiona Fui-Hoon Nah ; Chuan-Hoo Tan. Springer Verlag, 2016. pp. 270-279 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A genetic algorithm based model for chinese phishing E-commerce websites detection",

abstract = "We propose a new Chinese phishing e-commerce websites detection model which integrates the URL features and web features of websites. Some unique features of Chinese e-Commerce websites are included and Sequential Minimal Optimization (SMO) algorithm is applied to identify the phishing ecommerce websites. At the same time, we adopt the genetic algorithm (GA) to optimize the detection model. The evaluation results show that the performance of SMO algorithm is better than the baseline model and GA improves the detection accuracy significantly.",

keywords = "Chinese phishing website detection, E-commerce, Genetic algorithm, Sequential minimal optimization",

author = "Zhijun Yan and Su Liu and Hansi Jiang and Hangzhou Yang and Tianmei Wang and Baowen Sun",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 3rd International Conference on HCI in Business, Government, and Organizations: eCommerce and Innovation, HCIBGO 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 ; Conference date: 17-07-2016 Through 22-07-2016",

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doi = "10.1007/978-3-319-39396-4_25",

language = "English",

isbn = "9783319393957",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

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editor = "Nah, {Fiona Fui-Hoon} and Chuan-Hoo Tan",

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Yan, Z, Liu, S, Jiang, H, Yang, H, Wang, T & Sun, B 2016, A genetic algorithm based model for chinese phishing E-commerce websites detection. in FF-H Nah & C-H Tan (eds), HCI in Business, Government, and Organizations: eCommerce and Innovation - 3rd International Conference, HCIBGO 2016 and Held as Part of HCI International 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9751, Springer Verlag, pp. 270-279, 3rd International Conference on HCI in Business, Government, and Organizations: eCommerce and Innovation, HCIBGO 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016, Toronto, Canada, 17/07/16. https://doi.org/10.1007/978-3-319-39396-4_25

A genetic algorithm based model for chinese phishing E-commerce websites detection. / Yan, Zhijun; Liu, Su; Jiang, Hansi et al.
HCI in Business, Government, and Organizations: eCommerce and Innovation - 3rd International Conference, HCIBGO 2016 and Held as Part of HCI International 2016, Proceedings. ed. / Fiona Fui-Hoon Nah; Chuan-Hoo Tan. Springer Verlag, 2016. p. 270-279 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9751).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A genetic algorithm based model for chinese phishing E-commerce websites detection

AU - Yan, Zhijun

AU - Liu, Su

AU - Jiang, Hansi

AU - Yang, Hangzhou

AU - Wang, Tianmei

AU - Sun, Baowen

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - We propose a new Chinese phishing e-commerce websites detection model which integrates the URL features and web features of websites. Some unique features of Chinese e-Commerce websites are included and Sequential Minimal Optimization (SMO) algorithm is applied to identify the phishing ecommerce websites. At the same time, we adopt the genetic algorithm (GA) to optimize the detection model. The evaluation results show that the performance of SMO algorithm is better than the baseline model and GA improves the detection accuracy significantly.

AB - We propose a new Chinese phishing e-commerce websites detection model which integrates the URL features and web features of websites. Some unique features of Chinese e-Commerce websites are included and Sequential Minimal Optimization (SMO) algorithm is applied to identify the phishing ecommerce websites. At the same time, we adopt the genetic algorithm (GA) to optimize the detection model. The evaluation results show that the performance of SMO algorithm is better than the baseline model and GA improves the detection accuracy significantly.

KW - Chinese phishing website detection

KW - E-commerce

KW - Genetic algorithm

KW - Sequential minimal optimization

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - HCI in Business, Government, and Organizations

A2 - Nah, Fiona Fui-Hoon

A2 - Tan, Chuan-Hoo

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T2 - 3rd International Conference on HCI in Business, Government, and Organizations: eCommerce and Innovation, HCIBGO 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016

Y2 - 17 July 2016 through 22 July 2016

ER -

Yan Z, Liu S, Jiang H, Yang H, Wang T, Sun B. A genetic algorithm based model for chinese phishing E-commerce websites detection. In Nah FFH, Tan CH, editors, HCI in Business, Government, and Organizations: eCommerce and Innovation - 3rd International Conference, HCIBGO 2016 and Held as Part of HCI International 2016, Proceedings. Springer Verlag. 2016. p. 270-279. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-39396-4_25

A genetic algorithm based model for chinese phishing E-commerce websites detection

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