dc.contributor.author | Alhan, Birkan | |
dc.contributor.author | Gönen, Serkan | |
dc.contributor.author | Karacayılmaz, Gökçe | |
dc.contributor.author | Barışkan, Mehmet Ali | |
dc.contributor.author | Yılmaz, Ercan Nurcan | |
dc.date.accessioned | 2023-10-28T09:55:28Z | |
dc.date.available | 2023-10-28T09:55:28Z | |
dc.date.issued | 2022 | en_US |
dc.identifier.issn | 1330-3651 | |
dc.identifier.issn | 1848-6339 | |
dc.identifier.uri | https://hdl.handle.net/11363/6102 | |
dc.description.abstract | The rapid transition of all areas of our lives to the digital environment has kept people away from their intertwined social lives and made them dependent on the
isolated cyber environment. This dependency has led to increased cyber threats and, subsequently, cyber-attacks nationally or internationally. Due to the high cost of
cybersecurity systems and the expert nature of these systems' management, the cybersecurity component has been mostly ignored, especially in small and medium-sized
organizations. In this context, a holistic cybersecurity architecture is designed in which fully open source and free software and hardware-based Raspberry Pi devices with
low-cost embedded operating systems are used as a honeypot. In addition, the architectural structure has an integrated, flexible, and easily configurable end-to-end security
approach. It is suitable for different platforms by creating end-user screens with personalized software for network security guards and system administrators. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | UNIV OSIJEK, TECH FAC, TRG IVANE BRLIC-MAZURANIC 2, SLAVONSKI BROD HR-35000, CROATIA | en_US |
dc.relation.isversionof | 10.17559/TV-20210523121614 | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Cyber Security | en_US |
dc.subject | Honeypot | en_US |
dc.subject | Internet of Things | en_US |
dc.subject | LSTM | en_US |
dc.subject | Naive Bayes | en_US |
dc.title | Real-Time Cyber Attack Detection Over HoneyPi Using Machine Learning | en_US |
dc.type | article | en_US |
dc.relation.ispartof | Technical Gazette | en_US |
dc.department | Mühendislik ve Mimarlık Fakültesi | en_US |
dc.authorid | https://orcid.org/0000-0001-8529-1721 | en_US |
dc.authorid | https://orcid.org/0000-0001-9859-1600 | en_US |
dc.identifier.volume | 29 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.startpage | 1394 | en_US |
dc.identifier.endpage | 1401 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.institutionauthor | Alhan, Birkan | |
dc.institutionauthor | Gönen, Serkan | |
dc.institutionauthor | Barışkan, Mehmet Ali | |