PHISHING WEBSITE DETECTION USING WEIGHTED FEATURE LINE EMBEDDING

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IMANI MARYAM; MONTAZER GHOLAMALI

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Paper Information

Journal: THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY Year:2017 | Volume:9 | Issue:2 Page(s): 49-61

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Title

PHISHING WEBSITE DETECTION USING WEIGHTED FEATURE LINE EMBEDDING

Author(s)

IMANI MARYAM | MONTAZER GHOLAMALI | Issue Writer Certificate

Keywords

PHISHING DETECTION

FEATURE EXTRACTION

FEATURE LINE

VIRTUAL TRAINING

Abstract

The aim of phishing is tracing the users's private information without their permission by designing a new website which mimics the trusted website. The specialists of information technology do not agree on a unique definition for the discriminative features that characterizes the phishing websites. Therefore, the number of reliable training samples in PHISHING DETECTION problems is limited. Moreover, among the available training samples, there are abnormal samples that cause classification error. For instance, it is possible that there are phishing samples with similar features to legitimate ones and vice versa. A supervised FEATURE EXTRACTION method, called weighted FEATURE LINE embedding, is proposed in this paper to solve these problems. The proposed method virtually generates training samples by utilizing the FEATURE LINE metric. Hence, it can solve the small sample size problem. Moreover, by assigning appropriate weights to each pair of feature points, it corrects the undesirable quality of abnormal samples. The features extracted by our method improve the performance of phishing website detection specially by using small training sets.

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APA: Copy

IMANI, MARYAM, & MONTAZER, GHOLAMALI. (2017). PHISHING WEBSITE DETECTION USING WEIGHTED FEATURE LINE EMBEDDING. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, 9(2 ), 49-61. SID. https://sid.ir/paper/728062/en

Vancouver: Copy

IMANI MARYAM, MONTAZER GHOLAMALI. PHISHING WEBSITE DETECTION USING WEIGHTED FEATURE LINE EMBEDDING. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY[Internet]. 2017;9(2 ):49-61. Available from: https://sid.ir/paper/728062/en

IEEE: Copy

MARYAM IMANI, and GHOLAMALI MONTAZER, “PHISHING WEBSITE DETECTION USING WEIGHTED FEATURE LINE EMBEDDING,” THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, vol. 9, no. 2 , pp. 49–61, 2017, [Online]. Available: https://sid.ir/paper/728062/en

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