This article describes how sequential data modeling is a relevant task in Cybersecurity. Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent …
J Liu, Y Gao, F Hu - Computers & Security, 2021 - Elsevier
Network intrusion detection systems play an important role in protecting the network from attacks. However, Existing network intrusion data is imbalanced, which makes it difficult to …
Recently, Convolutional neural network (CNN) architectures in deep learning have achieved significant results in the field of computer vision. To transform this performance toward the …
With the rapid advancements of ubiquitous information and communication technologies, a large number of trustworthy online systems and services have been deployed. However …
SA Althubiti, EM Jones, K Roy - 2018 28th International …, 2018 - ieeexplore.ieee.org
Due to the massive amount of the network traffic, attackers have a great chance to cause a huge damage to the network system or its users. Intrusion detection plays an important role …
J Kim, Y Shin, E Choi - Journal of Multimedia Information System, 2019 - jmis.org
Abstract Machine-learning techniques have been actively employed to information security in recent years. Traditional rule-based security solutions are vulnerable to advanced attacks …
G Kim, H Yi, J Lee, Y Paek, S Yoon - arXiv preprint arXiv:1611.01726, 2016 - arxiv.org
In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. In this paper, we propose a system-call language …
An intrusion detection system (IDS) identifies whether the network traffic behavior is normal or abnormal or identifies the attack types. Recently, deep learning has emerged as a …
X Wang, S Yin, H Li, J Wang, L Teng - International Journal of Wireless …, 2020 - Springer
Network intrusion detection (NID) is an important method for network system administrators to detect various security holes. The performance of traditional NID methods can be affected …