LSTM-based system-call language modeling and robust ensemble method for designing host-based intrusion detection systems

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 …

Host based intrusion detection system with combined CNN/RNN model

A Chawla, B Lee, S Fallon, P Jacob - … 2018, IWAISe 2018, and Green Data …, 2019 - Springer
Cyber security has become one of the most challenging aspects of modern world digital
technology and it has become imperative to minimize and possibly avoid the impact of …

An approach for host-based intrusion detection system design using convolutional neural network

NN Tran, R Sarker, J Hu - … 2017, Melbourne, Australia, December 13-15 …, 2018 - Springer
Along with the drastic growth of telecommunication and networking, the cyber-threats are
getting more and more sophisticated and certainly leading to severe consequences. With …

A review on challenges and future research directions for machine learning-based intrusion detection system

A Thakkar, R Lohiya - Archives of Computational Methods in Engineering, 2023 - Springer
Research in the field of Intrusion Detection is focused on developing an efficient strategy that
can identify network attacks. One of the important strategies is to supervise the network …

Host-based intrusion detection using dynamic and static behavioral models

DY Yeung, Y Ding - Pattern recognition, 2003 - Elsevier
Intrusion detection has emerged as an important approach to network security. In this paper,
we adopt an anomaly detection approach by detecting possible intrusions based on …

A bidirectional LSTM deep learning approach for intrusion detection

Y Imrana, Y Xiang, L Ali, Z Abdul-Rauf - Expert Systems with Applications, 2021 - Elsevier
The rise in computer networks and internet attacks has become alarming for most service
providers. It has triggered the need for the development and implementation of intrusion …

[HTML][HTML] A scalable and hybrid intrusion detection system based on the convolutional-LSTM network

MA Khan, MR Karim, Y Kim - Symmetry, 2019 - mdpi.com
With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …

Empowering reinforcement learning on big sensed data for intrusion detection

S Otoum, B Kantarci, H Mouftah - Icc 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
Wireless sensor and actuator networks are widely adopted in various applications such as
critical infrastructure monitoring where sensory data in big volumes and velocity are prone to …

[HTML][HTML] Comparison of machine learning and deep learning models for network intrusion detection systems

N Thapa, Z Liu, DB Kc, B Gokaraju, K Roy - Future Internet, 2020 - mdpi.com
The development of robust anomaly-based network detection systems, which are preferred
over static signal-based network intrusion, is vital for cybersecurity. The development of a …

Applying machine learning to anomaly-based intrusion detection systems

F Yihunie, E Abdelfattah… - 2019 IEEE Long Island …, 2019 - ieeexplore.ieee.org
The enormous growth of Internet-based traffic exposes corporate networks with a wide
variety of vulnerabilities. Intrusive traffics are affecting the normal functionality of network's …