An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Recently, with the technological and digital revolution, the security of data is very crucial as a
massive amount of data is generated from various networks. Intrusion Detection System …
massive amount of data is generated from various networks. Intrusion Detection System …
Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model
S Aljawarneh, M Aldwairi, MB Yassein - Journal of Computational Science, 2018 - Elsevier
Efficiently detecting network intrusions requires the gathering of sensitive information. This
means that one has to collect large amounts of network transactions including high details of …
means that one has to collect large amounts of network transactions including high details of …
Anomaly based intrusion detection using filter based feature selection on KDD-CUP 99
P Kushwaha, H Buckchash… - TENCON 2017-2017 IEEE …, 2017 - ieeexplore.ieee.org
DoS, probing, phishing, website defacements etc. are the major problems being faced by the
network users these days. It has led to exposing of the network resources to the attackers …
network users these days. It has led to exposing of the network resources to the attackers …
Implementation of adaptive scheme in evolutionary technique for anomaly-based intrusion detection
Intrusion detection has become important to network security because of the increasing
connectivity between computers and internet. Various Intrusion Detection Systems have …
connectivity between computers and internet. Various Intrusion Detection Systems have …
An in-depth experimental study of anomaly detection using gradient boosted machine
BA Tama, KH Rhee - Neural Computing and Applications, 2019 - Springer
This paper proposes an improved detection performance of anomaly-based intrusion
detection system (IDS) using gradient boosted machine (GBM). The best parameters of GBM …
detection system (IDS) using gradient boosted machine (GBM). The best parameters of GBM …
Intrusion detection in networks using cuckoo search optimization
One of the key problems for researchers and network managers is anomaly detection in
network traffic. Anomalies in network traffic might signal a network intrusion, requiring the …
network traffic. Anomalies in network traffic might signal a network intrusion, requiring the …
An intelligent algorithm with feature selection and decision rules applied to anomaly intrusion detection
Intrusion detection system (IDS) is to monitor the attacks occurring in the computer or
networks. Anomaly intrusion detection plays an important role in IDS to detect new attacks …
networks. Anomaly intrusion detection plays an important role in IDS to detect new attacks …
Anomaly intrusion detection approach using hybrid MLP/CNN neural network
An anomaly intrusion detection approach based on hybrid MLP/CNN (multi-layer
perceptron/chaotic neural network) neural network is proposed in this paper. Most anomaly …
perceptron/chaotic neural network) neural network is proposed in this paper. Most anomaly …
A neural network based system for intrusion detection and attack classification
Anomaly based Intrusion Detection Systems (IDSs) are known to achieve high accuracy and
detection rate. However, a significant computational overhead is incurred in training and …
detection rate. However, a significant computational overhead is incurred in training and …
An anomaly-based intrusion detection system using recursive feature elimination technique for improved attack detection
PR Kannari, NS Chowdary, RL Biradar - Theoretical Computer Science, 2022 - Elsevier
The explosive growth of Internet and technologies has resulted in better life-changing
services to the society. This drastic change has invariably kept the users connected to the …
services to the society. This drastic change has invariably kept the users connected to the …