Sensor-based datasets for human activity recognition–a systematic review of literature
The research area of ambient assisted living has led to the development of activity
recognition systems (ARS) based on human activity recognition (HAR). These systems …
recognition systems (ARS) based on human activity recognition (HAR). These systems …
Particle swarm optimization and feature selection for intrusion detection system
The network traffic in the intrusion detection system (IDS) has unpredictable behaviour due
to the high computational power. The complexity of the system increases; thus, it is required …
to the high computational power. The complexity of the system increases; thus, it is required …
A survey on the development of self-organizing maps for unsupervised intrusion detection
X Qu, L Yang, K Guo, L Ma, M Sun, M Ke… - Mobile networks and …, 2021 - Springer
This paper describes a focused literature survey of self-organizing maps (SOM) in support of
intrusion detection. Specifically, the SOM architecture can be divided into two categories, ie …
intrusion detection. Specifically, the SOM architecture can be divided into two categories, ie …
Feature selection using particle swarm optimization in intrusion detection
I Ahmad - International Journal of Distributed Sensor …, 2015 - journals.sagepub.com
The prevention of intrusion in networks is decisive and an intrusion detection system is
extremely desirable with potent intrusion detection mechanism. Excessive work is done on …
extremely desirable with potent intrusion detection mechanism. Excessive work is done on …
A local feature engineering strategy to improve network anomaly detection
The dramatic increase in devices and services that has characterized modern societies in
recent decades, boosted by the exponential growth of ever faster network connections and …
recent decades, boosted by the exponential growth of ever faster network connections and …
Creating an explainable intrusion detection system using self organizing maps
Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems (IDS) are complex
black boxes. This means that a security analyst will have little to no explanation or …
black boxes. This means that a security analyst will have little to no explanation or …
Performance comparison of intrusion detection system based anomaly detection using artificial neural network and support vector machine
This study presents a comparison of the detection accuracy of ANN and SVM on the
anomaly-based IDS and uses all the features in the dataset. The experiments were …
anomaly-based IDS and uses all the features in the dataset. The experiments were …
Opposition learning based phases in artificial bee colony
Artificial bee colony (ABC) is a recently introduced swarm intelligence algorithm (SIA).
Initially only unconstrained problems were handled by ABC, which was later modified by …
Initially only unconstrained problems were handled by ABC, which was later modified by …
Enhancing Explainability and Trustworthiness of Intrusion Detection Systems Using Competitive Learning
Current AI-based Intrusion Detection Systems (IDS) primarily rely on untrustworthy black box
methods. Traditionally, many of these black box IDS are built using Error Based Learning …
methods. Traditionally, many of these black box IDS are built using Error Based Learning …
Neural networks as tool to improve the intrusion detection system
Nowadays, computer programs affecting computers both locally and network-wide have led
to the design and development of different preventive and corrective strategies to remedy …
to the design and development of different preventive and corrective strategies to remedy …