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Institution

Istanbul Kültür University

EducationIstanbul, Turkey
About: Istanbul Kültür University is a education organization based out in Istanbul, Turkey. It is known for research contribution in the topics: Raman spectroscopy & Apoptosis. The organization has 584 authors who have published 1058 publications receiving 17615 citations. The organization is also known as: Kültür University.


Papers
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Journal ArticleDOI
TL;DR: A heuristic rule called the smallest position value (SPV) borrowed from the random key representation of Bean was developed to enable the continuous particle swarm optimization algorithm to be applied to all classes of sequencing problems.

535 citations

Journal ArticleDOI
TL;DR: In this paper, the potential industrial applications of PCMs in textiles and clothing systems, the methods of PCM integration into textiles, and the method of evaluating their thermal properties are also presented.

531 citations

Journal ArticleDOI
TL;DR: In this article, a state-of-the-art report is focused on corrosion inhibitors used in concrete and is based on published studies in the last decade, focusing on the most commonly used inhibitors such as amino alcohols (AMAs), calcium nitrites (CN), and sodium monofluorophosphates (MFPs).

431 citations

Journal ArticleDOI
TL;DR: A real-time anti-phishing system, which uses seven different classification algorithms and natural language processing (NLP) based features, is proposed and Random Forest algorithm with only NLP based features gives the best performance with the 97.98% accuracy rate for detection of phishing URLs.
Abstract: Due to the rapid growth of the Internet, users change their preference from traditional shopping to the electronic commerce. Instead of bank/shop robbery, nowadays, criminals try to find their victims in the cyberspace with some specific tricks. By using the anonymous structure of the Internet, attackers set out new techniques, such as phishing, to deceive victims with the use of false websites to collect their sensitive information such as account IDs, usernames, passwords, etc. Understanding whether a web page is legitimate or phishing is a very challenging problem, due to its semantics-based attack structure, which mainly exploits the computer users’ vulnerabilities. Although software companies launch new anti-phishing products, which use blacklists, heuristics, visual and machine learning-based approaches, these products cannot prevent all of the phishing attacks. In this paper, a real-time anti-phishing system, which uses seven different classification algorithms and natural language processing (NLP) based features, is proposed. The system has the following distinguishing properties from other studies in the literature: language independence, use of a huge size of phishing and legitimate data, real-time execution, detection of new websites, independence from third-party services and use of feature-rich classifiers. For measuring the performance of the system, a new dataset is constructed, and the experimental results are tested on it. According to the experimental and comparative results from the implemented classification algorithms, Random Forest algorithm with only NLP based features gives the best performance with the 97.98% accuracy rate for detection of phishing URLs.

367 citations


Authors

Showing all 604 results

NameH-indexPapersCitations
John T Harvey8575937189
Erol Başar6828415981
Raoul François391455323
Sermin Genc34924133
Linet Özdamar32914929
Bahar Güntekin30922839
Görsev Yener281312490
Ahmet Karadağ251641987
Sevim Akyüz252012515
Cagatay Catal24882535
Ozgur Koray Sahingoz22992440
Chris Rumford22512193
Derya Durusu Emek-Savaş1736724
Zeki Ayağ17331573
Tanil Akyuz1667777
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20239
202224
202181
2020114
2019108
201875