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A lightweight double-stage scheme to identify malicious DNS over HTTPS traffic using a hybrid learning approach
The Domain Name System (DNS) protocol essentially translates domain names to IP
addresses, enabling browsers to load and utilize Internet resources. Despite its major role …
addresses, enabling browsers to load and utilize Internet resources. Despite its major role …
Ensemble machine learning techniques for accurate and efficient detection of botnet attacks in connected computers
The transmission of information, ideas, and thoughts requires communication, which is a
crucial component of human contact. The utilization of Internet of Things (IoT) devices is a …
crucial component of human contact. The utilization of Internet of Things (IoT) devices is a …
Hybrid metaheuristics with machine learning based botnet detection in cloud assisted internet of things environment
Botnet detection in a cloud-aided Internet of Things (IoT) environment is a tedious process,
meanwhile, IoT gadgets are extremely vulnerable to attacks due to poor security practices …
meanwhile, IoT gadgets are extremely vulnerable to attacks due to poor security practices …
Soil erosion status prediction using a novel random forest model optimized by random search method
Soil erosion, the degradation of the earth's surface through the removal of soil particles,
occurs in three phases: dislocation, transport, and deposition. Factors such as soil type …
occurs in three phases: dislocation, transport, and deposition. Factors such as soil type …
Feature selection for IoT botnet detection using equilibrium and Battle Royale Optimization
Abstract The Internet of Things (IoT) is rapidly expanding, bringing unprecedented
opportunities and significant security risks. Among the most appealing attacks on IoT are …
opportunities and significant security risks. Among the most appealing attacks on IoT are …
A hybrid model for botnet detection using machine learning
Botnet attacks are becoming a growing threat to the security of computer networks, and there
is a need for effective and efficient methods for detecting these attacks. In this study, we …
is a need for effective and efficient methods for detecting these attacks. In this study, we …
Modeling of botnet detection using chaotic binary Pelican Optimization Algorithm with deep learning on Internet of Things Environment
Nowadays, there are ample amounts of Internet of Things (IoT) devices interconnected to the
networks, and with technological improvement, cyberattacks and security threads, for …
networks, and with technological improvement, cyberattacks and security threads, for …
Intrusion Attack Detection Using Firefly Optimization Algorithm and Ensemble Classification Model
R Gangula, MM Vutukuru… - Wireless Personal …, 2023 - Springer
In recent decades, the Internet of Things (IoTs) based network intrusion detection (ID)
remains a challenging research topic. Currently, several machine-learning methodologies …
remains a challenging research topic. Currently, several machine-learning methodologies …
Anomaly detection in IOT edge computing using deep learning and instance-level horizontal reduction
The increasing number of network attacks has led to the development of intrusion detection
systems. However, these methods often face limitations such as high traffic flow data …
systems. However, these methods often face limitations such as high traffic flow data …
An Optimized Approach to Deep Learning for Botnet Detection and Classification for Cybersecurity in Internet of Things Environment.
A Alzahrani - Computers, Materials & Continua, 2024 - search.ebscohost.com
The recent development of the Internet of Things (IoTs) resulted in the growth of IoT-based
DDoS attacks. The detection of Botnet in IoT systems implements advanced cybersecurity …
DDoS attacks. The detection of Botnet in IoT systems implements advanced cybersecurity …