Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms
In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …
Deep ensemble-based efficient framework for network attack detection
Nowadays, networks play a critical role in business, education, and daily life, allowing
people to communicate via different platforms across long distances. However, such …
people to communicate via different platforms across long distances. However, such …
[PDF][PDF] IoT device identity management and blockchain for security and data integrity
Human-human or human-device communication has traditionally been the most prevalent
kind of communication, however, the Internet of Things (IoT) promises to dramatically …
kind of communication, however, the Internet of Things (IoT) promises to dramatically …
Introducing the UWF-ZeekDataFall22 Dataset to Classify Attack Tactics from Zeek Conn Logs Using Spark's Machine Learning in a Big Data Framework
This study introduces UWF-ZeekDataFall22, a newly created dataset labeled using the
MITRE ATT&CK framework. Although the focus of this research is on classifying the never …
MITRE ATT&CK framework. Although the focus of this research is on classifying the never …
[HTML][HTML] FAMTDS: A novel MFO-based fully automated malicious traffic detection system for multi-environment networks
Multi-environment networks, such as those in smart homes, handle both IoT and traditional
IP-based traffic. Weak security protocols in IoT devices and the diverse traffic flow make …
IP-based traffic. Weak security protocols in IoT devices and the diverse traffic flow make …
Disruptive effects of denial-of-service (DoS) attacks on microgrid distributed control: Altered communication topology, voltage stability, and accurate power allocation
Distributed control is an effective strategy for synchronizing actions among numerous
distributed generators (DGs) within a microgrid. This method adheres to specific …
distributed generators (DGs) within a microgrid. This method adheres to specific …
Comparative Analysis Between Feedforward Neural Network and CNN-LSTM Neural Network To Predict Household Electrical Energy Consumption
This paper compares the accuracy of energy prediction using Feedforward Neural Networks
(FNN) with a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) …
(FNN) with a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) …
[PDF][PDF] A Comparative Study of Distributed Denial of Service Attacks On The Inter-net Of Things By Using Shallow Neural Network
Abstract The Internet of Things (IoT) is a term used to indicate a world in which objects are
linked to the Internet. in some way, but not in the way that most people imagine. However, for …
linked to the Internet. in some way, but not in the way that most people imagine. However, for …
Analysis of Anomaly with Machine Learning Based Model for Detecting HTTP DDoS Attack
R Adila, AB Nusantara, MAR Putra… - … Conference on Green …, 2024 - ieeexplore.ieee.org
At present, almost every device is connected to the internet for communication. Information
also can be quickly obtained via the Internet. The Internet offers various helpful services like …
also can be quickly obtained via the Internet. The Internet offers various helpful services like …
Enhancing Network Security: Deep Ensemble-Based Attack Detection Framework
R Tamilkodi, S Ratalu, G Santoshi… - … in Advanced Artificial …, 2024 - books.google.com
Networks are significant in business, schooling, and day to day existence since they let
individuals converse with one another over significant distances utilizing a scope of devices …
individuals converse with one another over significant distances utilizing a scope of devices …