Performance Analysis of Machine Learning Algorithms in Intrusion …
Jan 1, 2020 · In addition, this work also aims for classifying the intrusions using ML algorithms like Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART) and Random Forest. The work was tested with the KDD-CUP dataset and their efficiency was measured and also compared along with the latest researches.
Intrusion Detection Systems using Linear Discriminant Analysis …
PDF | On Dec 1, 2015, Basant Subba and others published Intrusion Detection Systems using Linear Discriminant Analysis and Logistic Regression | Find, read and cite all the research...
Drawing on the application methods of deep learning in the field of natural language processing, we propose a novel model BAT-MC via the two phase’s learning of Linear Regression & 3 Layer Neural Network and attention on the time series features …
A secure edge computing model using machine learning and IDS …
Jun 1, 2024 · It addresses the security challenges arising from the rapid expansion of IoT and edge computing. The proposed Intrusion Detection System (IDS) combines Linear Discriminant Analysis (LDA) and Logistic Regression (LR) to swiftly and accurately identify intrusions without alerting neighboring devices.
Intrusion Detection Systems Using Machine Learning
Oct 10, 2023 · This paper has made use of the KDD CUP 99 and CICIDS 2017 intrusion detection system datasets to experiment with six common machine learning algorithms: Random Forest, Support Vector Machine, Neural network model, Gaussian Naïve Bayes, Logistic Regression and Linear Discriminant Analysis.
Network Intrusion Detection using Linear Regression
Mar 1, 2021 · Detecting intrusions can identify unknown attacks in a network and has been one of the successful ways to enhance network security. The current methods for identifying network anomalies are...
A Novel Intrusion Detection System Using Multiple Linear Regression
Conclusion The present study employs the Multiple Linear Regression (MLR) statistical technique to construct an Intrusion Detection System (IDS). To achieve this, the entirety of the data has been segregated into three distinct paths, which are …
Intrusion detection system based on machine learning using …
The network Intrusion Detection System (IDS) serves as the second line of defense behind the firewall and is responsible for accurately identifying hostile network attacks, providing real-time monitoring and dynamic security measures.
XMID-MQTT: explaining machine learning-based intrusion detection system ...
5 days ago · The growing dependence on the internet of things (IoT) across diverse applications underscores the need for robust security measures to safeguard these systems from numerous cyber threats. MQTT, a lightweight messaging protocol specifically designed for IoT, is particularly vulnerable to cyberattacks due to its extensive usage and inherent security complexities. Intrusion detection systems ...
Intrusion Detection System Utilizing Machine Learning Classifier ...
Oct 2, 2024 · Intrusion detection system can use linear discriminative analysis along with machine learning classifier algorithms for better results. The resultant robust system identifies different attacks in the network.