Feature Extraction and Classification Phishing Websites Based on URL

Aydin, Mustafa
Baykal, Nazife
In this study we extracted websites' URL features and analyzed subset based feature selection methods and classification algorithms for phishing websites detection.


Pilanci, Mehmet; Vural, Elif (2016-07-12)
We propose a domain adaptation algorithm that relies on a graph representation of data samples in the source and target domains. The algorithm combines the information of the known class labels in the source and target domains through the Fourier coefficients of the class label function in the two graphs. The proposed method does not require an ordering or a one-to-one mapping between the samples of the source and target domains; instead, it uses only a small set of matched pairs that serve the purpose of "...
Signature Based Vegetation Detection on Hyperspectral Images
Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Düzgün, Hafize Şebnem (2015-05-19)
In this study, the contribution of utilizing hyperspectral unmixing algorithms on signature based target detection algorithms is studied. Spectral Angle Mapper (SAM), Spectral Matched Filter (SMF) and Adaptive Cosine Estimator (ACE) algorithms are selected as target detection methods and the performance change related to the target spectral acquisition is evaluated. The spectral signature of the desired target, corn, is acquired from ASD hyperspectral library as well as from the hypespectral unmixing endmem...
Text Classification in the Turkish Marketing Domain for Context Sensitive Ad Distribution
Engin, Melih; Can, Tolga (2009-09-16)
In this paper, we construct and compare several feature extraction approaches in order to find a better solution for classification of Turkish web documents in the marketing domain. We produce our feature extraction techniques using characteristics of the Turkish language, structures of web documents and online content in the marketing domain. We form datasets in different feature spaces and we apply several Support Vector Machine (SVM) configurations on these datasets. We conduct our study considering the ...
Domain Adaptation with Nonparametric Projections
Vural, Elif (2019-08-22)
Domain adaptation algorithms focus on a setting where the training and test data are sampled from related but different distributions. Various domain adaptation methods aim to align the source and target domains in a new common domain by learning a transformation or projection. In this work, we learn a nonlinear and nonparametric projection of the source and target domains into a common domain along with a linear classifier in the new domain. Experiments on image data sets show that the proposed nonlinear a...
In praise of laziness: A lazy strategy for web information extraction
Ozcan, Rifat; Altıngövde, İsmail Sengör; Ulusoy, Özgür (2012-04-27)
A large number of Web information extraction algorithms are based on machine learning techniques. For such extraction algorithms, we propose employing a lazy learning strategy to build a specialized model for each test instance to improve the extraction accuracy and avoid the disadvantages of constructing a single general model.
Citation Formats
M. Aydin and N. Baykal, “Feature Extraction and Classification Phishing Websites Based on URL,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53940.