iNIDS: SWOT Analysis and TOWS Inferences of State-of-the-Art NIDS solutions for the development of Intelligent Network Intrusion Detection System
J Verma, A Bhandari, G Singh - Computer Communications, 2022 - Elsevier
Introduction: The growth of ubiquitous networked devices and the proliferation of
geographically dispersed 'Internet of Thing'devices have exponentially increased network …
geographically dispersed 'Internet of Thing'devices have exponentially increased network …
A systematic and comprehensive survey of recent advances in intrusion detection systems using machine learning: Deep learning, datasets, and attack taxonomy
Recently, intrusion detection systems (IDS) have become an essential part of most
organisations' security architecture due to the rise in frequency and severity of network …
organisations' security architecture due to the rise in frequency and severity of network …
Hybrid intrusion detection using mapreduce based black widow optimized convolutional long short-term memory neural networks
PR Kanna, P Santhi - Expert Systems with Applications, 2022 - Elsevier
The recent advancements in information and communication technologies have led to an
increasing number of online systems and services. These online systems can utilize …
increasing number of online systems and services. These online systems can utilize …
A hybrid deep learning model for efficient intrusion detection in big data environment
The volume of network and Internet traffic is expanding daily, with data being created at the
zettabyte to petabyte scale at an exceptionally high rate. These can be characterized as big …
zettabyte to petabyte scale at an exceptionally high rate. These can be characterized as big …
A novel two-stage deep learning model for efficient network intrusion detection
The network intrusion detection system is an important tool for protecting computer networks
against threats and malicious attacks. Many techniques have recently been proposed; …
against threats and malicious attacks. Many techniques have recently been proposed; …
A novel scalable intrusion detection system based on deep learning
This paper successfully tackles the problem of processing a vast amount of security related
data for the task of network intrusion detection. It employs Apache Spark, as a big data …
data for the task of network intrusion detection. It employs Apache Spark, as a big data …
A scalable and hybrid intrusion detection system based on the convolutional-LSTM network
With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …
large number of trustworthy online systems and services have been deployed. However …
Federated TON_IoT Windows datasets for evaluating AI-based security applications
N Moustafa, M Keshky, E Debiez… - 2020 IEEE 19th …, 2020 - ieeexplore.ieee.org
Existing cyber security solutions have been basically developed using knowledge-based
models that often cannot trigger new cyber-attack families. With the boom of Artificial …
models that often cannot trigger new cyber-attack families. With the boom of Artificial …
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 …
Data analytics-enabled intrusion detection: Evaluations of ToN_IoT linux datasets
N Moustafa, M Ahmed, S Ahmed - 2020 IEEE 19th International …, 2020 - ieeexplore.ieee.org
With the widespread of Artificial Intelligence (AI)-enabled security applications, there is a
need for collecting heterogeneous and scalable data sources for effectively evaluating the …
need for collecting heterogeneous and scalable data sources for effectively evaluating the …