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

Halim Görkem GÜLMEZ; Pelin ANGIN

doi:https://doi.org/10.35377/saucis.04.01.834048

Makale detayları

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

Yazarlar:

Halim Görkem GÜLMEZ | Pelin ANGIN

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Sakarya University Journal of Computer and Information Sciences 2021 Vol.4 Issue 1, pp.11-25

Belge Tipi:

Makale

Yayın Tarihi:

4/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000551922

DOI:

https://doi.org/10.35377/saucis.04.01.834048

Özet:

 

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.

Makale detayları

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

Yazarlar: Halim Görkem GÜLMEZ | Pelin ANGIN

Ana Başlıklar: Veri işleme & bilgisayar bilimi

Dergi: Sakarya University Journal of Computer and Information Sciences 2021 Vol.4 Issue 1, pp.11-25

Belge Tipi: Makale

Yayın Tarihi: 4/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000551922

DOI: https://doi.org/10.35377/saucis.04.01.834048

Sayı

Yazarlar:

Halim Görkem GÜLMEZ | Pelin ANGIN

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Sakarya University Journal of Computer and Information Sciences 2021 Vol.4 Issue 1, pp.11-25

Belge Tipi:

Makale

Yayın Tarihi:

4/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000551922

DOI:

https://doi.org/10.35377/saucis.04.01.834048