Network anomaly uncovering on CICIDS-2017 dataset: a supervised artificial intelligence approach

P Jairu, AB Mailewa - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
In today's world, businesses and services are shifted to a digital transformation. As a result,
network traffic has tremendously increased over the years. With that, network threats and …

Novel Approach for Network Anomaly Detection Using Autoencoder on CICIDS Dataset

R Singh, N Srivastava, A Kumar - International Conference on Information …, 2023 - Springer
Through widespread internet protocols and network standards, networking services are
accessible. Insecure communication and assaults on traffic networks must be taken into …

Novel Machine Learning Technique for Intrusion Detection in Recent Network-based Attacks

A Srivastava, A Agarwal, G Kaur - 2019 4th International …, 2019 - ieeexplore.ieee.org
Intrusion Detection is a vastly growing area. Traditionally supervised learning techniques
were used for detecting intrusions in the network traffic data. But nowadays not only the rate …

Detecting intrusions and attacks in the network traffic using anomaly based techniques

V Kumar, V Choudhary, V Sahrawat… - 2020 5th International …, 2020 - ieeexplore.ieee.org
Technology has become the backbone of today's Information and Communication
Technology. Today a large number of transactions are carried out online and thus possess a …

Machine learning mechanisms for network anomaly detection system: A review

S Singh, S Banerjee - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Network Anomaly Detection Systems (NADS) has a great importance in Network Defense
System for detecting potential or critical threats. Numerous Organization have actualized …

Network traffic anomaly detection based on Apache Spark

PH Pwint, T Shwe - 2019 international conference on …, 2019 - ieeexplore.ieee.org
With the growing amount of internet and IoT traffic across the network, network anomaly
detection system has become a popular and useful strategy to detect anomalies, attacks and …

Anomaly-based intrusion detection system using one-dimensional convolutional neural network

AT Assy, Y Mostafa, A Abd El-khaleq… - Procedia Computer …, 2023 - Elsevier
As technologies in information and virtualization evolve, the volume of security threats
attempting to cause damage to systems grows and becomes more powerful, which …

Evaluation of machine learning techniques for network intrusion detection

M Zaman, CH Lung - NOMS 2018-2018 IEEE/IFIP Network …, 2018 - ieeexplore.ieee.org
Network traffic anomaly may indicate a possible intrusion in the network and therefore
anomaly detection is important to detect and prevent the security attacks. The early research …

Anomaly-based intrusion detection using machine learning: An ensemble approach

R Lalduhsaka, N Bora, AK Khan - International Journal of Information …, 2022 - igi-global.com
Intrusion detection systems were developed to detect any suspicious traffic in the network.
Conventional intrusion detection comes with its sets of limitations. The authors aimed to …

[PDF][PDF] Network anomaly detection by means of machine learning: random forest approach with apache spark

H Hajialian, C Toma - Informatica Economica, 2018 - revistaie.ase.ro
Nowadays the network security is a crucial issue and traditional intrusion detection systems
are not a sufficient way. Hence the intelligent detection systems should have a major role in …