LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the k-Barriers for Intrusion Detection Using …
The dramatic increase in the computational facilities integrated with the explainable
machine learning algorithms allows us to do fast intrusion detection and prevention at …
machine learning algorithms allows us to do fast intrusion detection and prevention at …
AutoML-ID: Automated machine learning model for intrusion detection using wireless sensor network
Momentous increase in the popularity of explainable machine learning models coupled with
the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient …
the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient …
[HTML][HTML] A deep learning based feed forward artificial neural network to predict the K-barriers for intrusion detection using a wireless sensor network
Abstract Wireless Sensor Networks (WSN) has a wide range of opportunities and can be
applied to almost every part of our life. Intrusion detection and monitoring across disputed …
applied to almost every part of our life. Intrusion detection and monitoring across disputed …
A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks
Abstract Wireless Sensor Networks (WSNs) is a promising technology with enormous
applications in almost every walk of life. One of the crucial applications of WSNs is intrusion …
applications in almost every walk of life. One of the crucial applications of WSNs is intrusion …
P2CA-GAM-ID: Coupling of probabilistic principal components analysis with generalised additive model to predict the k− barriers for intrusion detection
Drastic advancement in computing technology and the dramatic increase in the usage of
explainable machine learning algorithms provide a promising platform for developing robust …
explainable machine learning algorithms provide a promising platform for developing robust …
A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks
Abstract Sensors in a Wireless Sensor Network (WSN) sense, process, and transmit
information simultaneously. They mainly find applications in agriculture monitoring …
information simultaneously. They mainly find applications in agriculture monitoring …
A Deep Learning‐Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks
An intrusion detection system, often known as an IDS, is extremely important for preventing
attacks on a network, violating network policies, and gaining unauthorized access to a …
attacks on a network, violating network policies, and gaining unauthorized access to a …
A hybrid intrusion detection model using ega-pso and improved random forest method
AK Balyan, S Ahuja, UK Lilhore, SK Sharma… - Sensors, 2022 - mdpi.com
Due to the rapid growth in IT technology, digital data have increased availability, creating
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
Hybrid optimized deep neural network with enhanced conditional random field based intrusion detection on wireless sensor network
Security plays an important part in this Internet world because of the hasty improvement of
Internet customers. Different Intrusion Detection Systems (IDS) have been advanced for …
Internet customers. Different Intrusion Detection Systems (IDS) have been advanced for …
A deep learning method with filter based feature engineering for wireless intrusion detection system
SM Kasongo, Y Sun - IEEE access, 2019 - ieeexplore.ieee.org
In recent years, the increased use of wireless networks for the transmission of large volumes
of information has generated a myriad of security threats and privacy concerns; …
of information has generated a myriad of security threats and privacy concerns; …