Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
[PDF][PDF] Analysis of KDD CUP 99 dataset using clustering based data mining
MK Siddiqui, S Naahid - … Journal of Database Theory and Application, 2013 - academia.edu
The KDD Cup 99 dataset has been the point of attraction for many researchers in the field of
intrusion detection from the last decade. Many researchers have contributed their efforts to …
intrusion detection from the last decade. Many researchers have contributed their efforts to …
Anomaly-based IDS to detect attack using various artificial intelligence & machine learning algorithms: a review
A Mishra, P Yadav - 2nd International Conference on Data …, 2020 - ieeexplore.ieee.org
Cyber-attacks are becoming more complex & increasing tasks in accurate intrusion
detection (ID). Failure to avoid intrusion can reduce the reliability of security services, for …
detection (ID). Failure to avoid intrusion can reduce the reliability of security services, for …
Network attack detection using an unsupervised machine learning algorithm
With the increase in network connectivity in today's web-enabled environments, there is an
escalation in cyber-related crimes. This increase in illicit activity prompts organizations to …
escalation in cyber-related crimes. This increase in illicit activity prompts organizations to …
Detecting DDoS attacks using decision tree algorithm
S Lakshminarasimman, S Ruswin… - … conference on signal …, 2017 - ieeexplore.ieee.org
The Wide-reaching usage of the standard called as IEEE 802.111 has been acting as a
solution to support aggressive network coverage with high bandwidth raised various security …
solution to support aggressive network coverage with high bandwidth raised various security …
DDAM: detecting DDoS attacks using machine learning approach
K Narasimha Mallikarjunan, A Bhuvaneshwaran… - … , Applications and Future …, 2018 - Springer
Abstract Dealing the Distributed Denial of Service (DDoS) attack is a continuing challenge in
the field of network security. An Intrusion Detection System (IDS) is one of the solutions to …
the field of network security. An Intrusion Detection System (IDS) is one of the solutions to …
Meta‐analysis and systematic review for anomaly network intrusion detection systems: Detection methods, dataset, validation methodology, and challenges
Intrusion detection systems built on artificial intelligence (AI) are presented as latent
mechanisms for actively detecting fresh attacks over a complex network. The authors used a …
mechanisms for actively detecting fresh attacks over a complex network. The authors used a …
An intrusion detection system based on neural network
O Can, OK Sahingoz - 2015 23nd Signal Processing and …, 2015 - ieeexplore.ieee.org
In current time, cyber wars are added in military operation areas. Some measures reduce
amount of attacks but these measures can't block cyber attacks completely so it is important …
amount of attacks but these measures can't block cyber attacks completely so it is important …
A Combined Multi-Classification Network Intrusion Detection System Based on Feature Selection and Neural Network Improvement
Y Wang, Z Liu, W Zheng, J Wang, H Shi, M Gu - Applied Sciences, 2023 - mdpi.com
Featured Application Increased parallelism in edge network security issues, Feature loss
handling. Abstract Feature loss in IoT scenarios is a common problem. This situation poses …
handling. Abstract Feature loss in IoT scenarios is a common problem. This situation poses …
[PDF][PDF] Intrusion detection and attack classification using back-propagation neural network
R Gaidhane, C Vaidya, M Raghuwanshi - Int. J. Eng. Res, 2014 - academia.edu
Intrusion detection is a process that analyzes abnormalities in system or network activities.
For security purpose it is necessary to identify malicious events correctly. Majority of …
For security purpose it is necessary to identify malicious events correctly. Majority of …