Machine learning techniques for anomaly-based detection system on CSE-CIC-IDS2018 dataset
Anomaly-based detection is a novel form of an intrusion detection system, which has
become the focus of many researchers for cybersecurity systems. Data manages most …
become the focus of many researchers for cybersecurity systems. Data manages most …
Performance evaluation of a combined anomaly detection platform
Hybrid Anomaly Detection Model (HADM) is a platform that filters network traffic and
identifies malicious activities on the network. The platform applies data mining techniques to …
identifies malicious activities on the network. The platform applies data mining techniques to …
Anomaly detection using ensemble techniques for boosting the security of intrusion detection system
IoT-based applications have witnessed a rapid surge in deployment in various domains. IoT
infrastructure is the nervous system responsible for the effective functioning of Smart Cities …
infrastructure is the nervous system responsible for the effective functioning of Smart Cities …
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 …
network traffic has tremendously increased over the years. With that, network threats and …
Anomaly detection for cyber-security based on convolution neural network: A survey
The expanding growth of computer and communication technologies results in a vast
amount of security concerns. Various types of cyber-security enabled mechanisms have …
amount of security concerns. Various types of cyber-security enabled mechanisms have …
An isolation forest learning based outlier detection approach for effectively classifying cyber anomalies
Cybersecurity has recently gained considerable interest in today's security issues because
of the popularity of the Internet-of-Things (IoT), the considerable growth of mobile networks …
of the popularity of the Internet-of-Things (IoT), the considerable growth of mobile networks …
Novel framework for anomaly detection using machine learning technique on CIC-IDS2017 dataset
R Singh, G Srivastav - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
There are various deep learning-based IDS techniques are implemented in large scale.
Intrusion detection systems are critical components for protecting ICT infrastructure (IDSs) …
Intrusion detection systems are critical components for protecting ICT infrastructure (IDSs) …
[HTML][HTML] Anomaly detection optimization using big data and deep learning to reduce false-positive
Abstract Anomaly-based Intrusion Detection System (IDS) has been a hot research topic
because of its ability to detect new threats rather than only memorized signatures threats of …
because of its ability to detect new threats rather than only memorized signatures threats of …
MLTs-ADCNs: Machine learning techniques for anomaly detection in communication networks
From a security perspective, the research of the jeopardized 6G wireless communications
and its expected ultra-densified ubiquitous wireless networks urge the development of a …
and its expected ultra-densified ubiquitous wireless networks urge the development of a …
CICIDS-2017 dataset feature analysis with information gain for anomaly detection
Feature selection (FS) is one of the important tasks of data preprocessing in data analytics.
The data with a large number of features will affect the computational complexity, increase a …
The data with a large number of features will affect the computational complexity, increase a …