Dr. Ahmet Selman Bozkir

Tätigkeit an der ZHAW als

Senior Researcher

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Computer Vision, Informationssicherheit, Phishing-Erkennung, Phishing-Erkennung, Malware-Erkennung, visuelle Ähnlichkeit, Text Mining, Entscheidungsunterstützungssysteme, Computerfotografie, Data Mining für Bildungszwecke

• OptiPhish - Effective and Measurable Phishing Awareness Training / Teammitglied / Projekt laufend
• Standardized Data and Modeling for AI-based CoVID-19 Diagnosis Support on CT Scans (SDMCT) / Teammitglied / Projekt abgeschlossen

• Amirian, Mohammadreza; Montoya, Javier; Gruss, Jonathan; Stebler, Yves D.; Bozkir, Ahmet Selman; Calandri, Marco; Schwenker, Friedhelm; Stadelmann, Thilo,

  2021.

  PrepNet : a convolutional auto-encoder to homogenize CT scans for cross-dataset medical image analysis [Paper].

  In:

  Proceedings of CISP-BMEI’21.

  14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Shanghai, China, 23-25 October 2021.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Verfügbar unter: https://doi.org/10.21256/zhaw-23318

SCI/E SSCI Journals
Bozkir, A.S., Tahillioglu, E., Aydos, M., Kara, I., Catch Them Alive: A Malware Detection Approach through Memory Forensics, Manifold Learning and Computer Vision, Computers & Security, 2021

Kingir, S., Gok, B.,Bozkir, A.S., Exploring Relations Among Motivational Beliefs, Learning Strategies and Constructivist Learning Environment Perceptions Through Unsupervised Learning, Journal of Baltic Science Education 19(5), pp.804-823, 2020 Doi: 10.33225/jbse/20.19.804

Bozkir, A.S.,Aydos, M., LogoSENSE: A Companion HOG based Logo Detection Scheme for Phishing Web Page and E-mail Brand Recognition, Computers & Security, 95C., 2020 Doi: 10.1016/j.cose.2020.101855

Bozkir, A.S.,Akcapinar Sezer, E., Layout-based computation of web page similarity ranks, International Journal of Human-Computer Studies, 110, pp.95-114., 2018 Doi: 10.1016/j.ijhcs.2017.10.008

Bozkir, A.S.,Akcapinar Sezer, E., FUAT: A fuzzy clustering analysis tool, Expert Systems with Applications, 40(3), pp.842-849., 2013. Doi: doi:10.1016/j.eswa.2012.05.038

Nefeslioglu, H.A.,Akcapinar Sezer, Gokceoglu, C., Bozkir, A.S.,Duman, T.Y., Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul Turkey, Mathematical Problems in Engineering, pp.1-15., 2010. Doi: 10.1155/2010/901095


Book Chapters

Bozkir, A.S., Nefeslioglu, H.A., Kartal, O., Akcapinar Sezer, E., Gokceoglu. C., Geological Strength Index (GSI) Determination By Local Image Descriptors And Machine Learning Methods, Human Computer Interaction, Nova Publications, USA, Editor:Turgut Özseven, ISBN:978-1-53616-495-4, 2020

Bozkir, A.S., Akcapinar Sezer, E., SimiLay: A Developing Web Page Layout Based Visual Similarity Search Engine, Lecture Notes in Artificial Intelligence, Springer-Verlag Berlin, Germany, Editor:Petra Perner, ISBN:978-3-319-08979-9, 2014

Bozkir, A.S., Mazman, S. G., Akcapinar Sezer, E., Identification of User Patterns in Social Networks by Data Mining Techniques: Facebook Case, Technological Convergence and Social Networks in Information Management, Springer Berlin Heidelberg, Editor: Serap Kurbanoglu Serap, Umut Al, ISBN:978-3-642-16031-8, 2010

Conferences

Bozkir, A.S., Nefeslioglu, H., Kartal, O., Sezer, E., Cokceoglu, C., Geological strength index prediction by vision and machine learning methods, ISRM International Symposium Eurock 2020 – Hard Rock Engineering, Trondheim, Norway, 2020

Dalgic, F.C.,Bozkir, A.S., Aydos, M., Phish-IRIS: A New Approach for Vision Based Brand Prediction of Phishing Web Pages via Compact Visual Descriptors, ISMSIT, Ankara, Turkey, 2018

Bozkir, A.S., Akcapinar Sezer, E., Use of HOG Descriptors in Phishing Detection, 4th International Symposium On Digital Forencic and Security (ISDFS), pp.148-153., Arkansas, USA, 2016

Naderalvojoud, B., Bozkir, A.S.,Sezer, E., Investigation of Term Weighting Schemes In Classification Of Imbalanced Texts, Machine Learning and Data Mining in Pattern Recognition (MLDM 2014), pp.39-46., Lisbon, Portugal, 2014

Bozkir, A.S., Cankaya, O. A., Aydos, M., Utilization and Comparision of Convolutional Neural Networks in Malware Recognition, Sinyal Isleme ve Uygulamalari Kurultayi SIU 2019, Sivas, Turkey, 2019

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