Real-Time Cyber Attack Detection Over HoneyPi Using Machine Learning

2Citations
Citations of this article
42Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Alhan, B., Gönen, S., Karacayilmaz, G., Barişkan, M. A., & Yilmaz, E. N. (2022). Real-Time Cyber Attack Detection Over HoneyPi Using Machine Learning. Tehnicki Vjesnik, 29(4), 1394–1401. https://doi.org/10.17559/TV-20210523121614

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free