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Using Attribute-bas...
Using Attribute-based Feature Selection Approaches and Machine Learning Algorithms for Detecting Fraudulent Website URLs
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- Aydin, Mustafa (författare)
- Orta Doğu Teknik Üniversitesi,Middle East Technical University (METU)
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- Butun, Ismail, 1981 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Bicakci, Kemal (författare)
- TOBB University of Economics and Technology
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- Baykal, Nazife (författare)
- Orta Doğu Teknik Üniversitesi,Middle East Technical University (METU)
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(creator_code:org_t)
- 2020
- 2020
- Engelska.
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Ingår i: 2020 10th Annual Computing and Communication Workshop and Conference, CCWC 2020. ; , s. 774-779
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https://research.cha...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Phishing is a malicious form of online theft and needs to be prevented in order to increase the overall trust of the public on the Internet. In this study, for that purpose, the authors present their findings on the methods of detecting phishing websites. Data mining algorithms along with classifier algorithms are used in order to achieve a satisfactory result. In terms of classifiers, the Naïve Bayes, SMO, and J48 algorithms are used. As for the feature selection algorithm; Gain Ratio Attribute and ReliefF Attribute are selected. The results are provided in a comparative way. Accordingly; SMO and J48 algorithms provided satisfactory results in the detection of phishing websites, however, Naïve Bayes performed poor and is the least recommended method among all.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Data analysis
- Cyber theft
- Machine learning algorithms
- Fraudulent website detection
- Attribute-based feature selection
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)