Intrusion detection system using hybrid classifiers with meta-heuristic algorithms for the optimization and feature selection by genetic algorithm
An intrusion detection system (IDS) is considered critical for detecting threats, intrusions, and
unauthorized access. IDS monitors massive network traffic that includes irrelevant and …
unauthorized access. IDS monitors massive network traffic that includes irrelevant and …
Optimized extreme learning machine for detecting DDoS attacks in cloud computing
GS Kushwah, V Ranga - Computers & Security, 2021 - Elsevier
Distributed denial of service (DDoS) attack is a serious security threat to cloud computing
that affects the availability of cloud services. Therefore, defending against these attacks …
that affects the availability of cloud services. Therefore, defending against these attacks …
Identifying and benchmarking key features for cyber intrusion detection: an ensemble approach
A Binbusayyis, T Vaiyapuri - IEEE Access, 2019 - ieeexplore.ieee.org
In today's interconnected era, intrusion detection system (IDS) has the potential to be the
frontier of defense against cyberattacks and plays an essential role in achieving security of …
frontier of defense against cyberattacks and plays an essential role in achieving security of …
[HTML][HTML] Ensemble classifiers for network intrusion detection using a novel network attack dataset
Due to the extensive use of computer networks, new risks have arisen, and improving the
speed and accuracy of security mechanisms has become a critical need. Although new …
speed and accuracy of security mechanisms has become a critical need. Although new …
[HTML][HTML] Prediction of rock mass class ahead of TBM excavation face by ML and DL algorithms with Bayesian TPE optimization and SHAP feature analysis
In this paper, field construction data from the Singapore Metro Line project were used to
study the mapping relationship and establish the prediction model between TBM operation …
study the mapping relationship and establish the prediction model between TBM operation …
Building an effective intrusion detection system by using hybrid data optimization based on machine learning algorithms
J Ren, J Guo, W Qian, H Yuan, X Hao… - Security and …, 2019 - Wiley Online Library
Intrusion detection system (IDS) can effectively identify anomaly behaviors in the network;
however, it still has low detection rate and high false alarm rate especially for anomalies with …
however, it still has low detection rate and high false alarm rate especially for anomalies with …
Feature selection techniques in the context of big data: taxonomy and analysis
Abstract Recent advancements in Information Technology (IT) have engendered the rapid
production of big data, as enormous volumes of data with high dimensional features grow …
production of big data, as enormous volumes of data with high dimensional features grow …
Designing an efficient security framework for detecting intrusions in virtual network of cloud computing
Cloud computing has grown for various IT capabilities such as IoTs, Mobile Computing,
Smart IT, etc. However, due to the dynamic and distributed nature of cloud and …
Smart IT, etc. However, due to the dynamic and distributed nature of cloud and …
[HTML][HTML] A novel ensemble learning-based model for network intrusion detection
The growth of Internet and the services provided by it has been growing exponentially in the
past few decades. With such growth, there is also an ever-increasing threat to the security of …
past few decades. With such growth, there is also an ever-increasing threat to the security of …
An improved design for a cloud intrusion detection system using hybrid features selection approach with ML classifier
The focus of cloud computing nowadays has been reshaping the digital epoch, in which
clients now face serious concerns about the security and privacy of their data hosted in the …
clients now face serious concerns about the security and privacy of their data hosted in the …