Institution
Istanbul Kültür University
Education•Istanbul, 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 published on a yearly basis
Papers
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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
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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
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484 citations
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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
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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
Name | H-index | Papers | Citations |
---|---|---|---|
John T Harvey | 85 | 759 | 37189 |
Erol Başar | 68 | 284 | 15981 |
Raoul François | 39 | 145 | 5323 |
Sermin Genc | 34 | 92 | 4133 |
Linet Özdamar | 32 | 91 | 4929 |
Bahar Güntekin | 30 | 92 | 2839 |
Görsev Yener | 28 | 131 | 2490 |
Ahmet Karadağ | 25 | 164 | 1987 |
Sevim Akyüz | 25 | 201 | 2515 |
Cagatay Catal | 24 | 88 | 2535 |
Ozgur Koray Sahingoz | 22 | 99 | 2440 |
Chris Rumford | 22 | 51 | 2193 |
Derya Durusu Emek-Savaş | 17 | 36 | 724 |
Zeki Ayağ | 17 | 33 | 1573 |
Tanil Akyuz | 16 | 67 | 777 |