A Study on the Efficacy of Deep Reinforcement Learning for Intrusion Detection

2021-04-01
GÜLMEZ, HALİM GÖRKEM
Angın, Pelin
Show full item record
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
309
views
236
downloads
The world has witnessed a fast-paced digital transformation in the past decade, giving rise to all-connected environments. While the increasingly widespread availability of networks has benefited many aspects of our lives, providing the necessary infrastructure for smart autonomous systems, it has also created a large cyber attack surface. This has made real-time network intrusion detection a significant component of any computerized system. With the advances in computer hardware architectures with fast, high-volume data processing capabilities and the developments in the field of artificial intelligence, deep learning has emerged as a significant aid for achieving accurate intrusion detection, especially for zero-day attacks. In this paper, we propose a deep reinforcement learning-based approach for network intrusion detection and demonstrate its efficacy using two publicly available intrusion detection datasets, namely NSL-KDD and UNSW-NB15. The experiment results suggest that deep reinforcement learning has significant potential to provide effective intrusion detection in the increasingly complex networks of the future.
security, deep reinforcement learning, intrusion detection
http://dx.doi.org/10.35377/saucis.04.01.834048
https://hdl.handle.net/11511/97149
Sakarya University Journal of Computer and Information Sciences
Department of Computer Engineering, Article

Suggestions

EXPLORING THE MEANING IN PLATFORM-BASED DESIGN WORK FROM THE PERSPECTIVE OF INDUSTRIAL DESIGNERS
Dilek, İrem; Töre Yargın, Gülşen; Kaygan, Pınar; Department of Industrial Design (2021-10-18)
Over the past decade the world of work has been experiencing digital transformation. Integrating the digital processes and tools into business models, digital transformation has led to the shift in the traditional business structures, hierarchies, relations, and the workplace. Thanks to this shift in the traditional way of work, today, it is possible to outsource the work through an open call to a geographically dispersed mass of people. This means that, companies or individuals now have access to an indefi...
A Comparative study of learning based control policies and conventional controllers on 2D bi-rotor platform with tail assistance
Uğurlu, Halil İIbrahim; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2019)
With the developing technology, multi-rotor platforms have become widespread and their control has become an important problem. In this thesis, we analyze physical extensions and control approaches for better control of rotor platforms. The first main contribution of the thesis is whether a tail-appendage that is attached under a multi-rotor platform can improve the multi-rotor's performance. Moreover, we used conventional control approaches as well as Deep Reinforcement Learning to learn a policy for contr...
A Multi-camera system for automation of mouse grimace scaling using convolutional neural networks
Ağca, Ahmet; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2019)
Over the past decade, convolutional neural networks (CNNs) have gained great progress on the area of computer vision. Many problems related to automation of image recognition or classification are now possible to be solved using CNN with an accuracy much more than a human can achieve. One of these problems is the automation of Mouse Grimace Scaling (MGS). It is such a time consuming and error-prone task even for an expert to classify the pain levels of a mouse for lots of images captured from videos. For th...
A Usability study on electronic document management system in Middle East Technical University
Karagöz, Alpay; Özkan Yıldırım, Sevgi; Department of Information Systems (2013)
The development of information technologies (IT) in recent years has started to affect the daily routines of the people. These technologies have changed the way that the things are done. One of these technologies is Electronic Document Management System. Considering the increasing amount of documents needed for the institutions, it could be said that there was a need for a system to manage this complexity. However, usability of such technologies depend on the people who would use the system. Usability probl...
A Deep reinforcement learning approach to network intrusion detection
Gülmez, Halim Görkem; Angın, Pelin; Department of Computer Engineering (2019)
Intrusion detection is one of the most important problems in today’s world. Every daynew attacks are being used in order to breach the security of systems and signature-based security systems fail to detect these zero-day attacks. An anomaly-basedintrusion detection system, particularly one that utilizes a machine learning approach,is needed to effectively handle these kinds of attacks. With the advancements in bigdata technologies, storing and handling data became easier, therefore big dataanalytics has be...
Citation Formats
H. G. GÜLMEZ and P. Angın, “A Study on the Efficacy of Deep Reinforcement Learning for Intrusion Detection,” Sakarya University Journal of Computer and Information Sciences, vol. 4, no. 1, pp. 11–25, 2021, Accessed: 00, 2022. [Online]. Available: http://dx.doi.org/10.35377/saucis.04.01.834048.
METU IIS - Integrated Information Service open@metu.edu.tr