Machine-learning-based darknet traffic detection system for IoT applications
The massive modern technical revolution in electronics, cognitive computing, and sensing
has provided critical infrastructure for the development of today's Internet of Things (IoT) for a …
has provided critical infrastructure for the development of today's Internet of Things (IoT) for a …
Darkdetect: Darknet traffic detection and categorization using modified convolution-long short-term memory
Darknet is commonly known as the epicenter of illegal online activities. An analysis of
darknet traffic is essential to monitor real-time applications and activities running over the …
darknet traffic is essential to monitor real-time applications and activities running over the …
Darknet traffic classification using machine learning techniques
LA Iliadis, T Kaifas - … conference on modern circuits and systems …, 2021 - ieeexplore.ieee.org
A Darknet is an overlay network within the Internet, and packets' traffic originating from it is
usually termed as suspicious. In this paper common machine learning classification …
usually termed as suspicious. In this paper common machine learning classification …
DarknetSec: A novel self-attentive deep learning method for darknet traffic classification and application identification
J Lan, X Liu, B Li, Y Li, T Geng - Computers & Security, 2022 - Elsevier
Darknet traffic classification is crucial for identifying anonymous network applications and
defensing cyber crimes. Although notable research efforts have been dedicated to …
defensing cyber crimes. Although notable research efforts have been dedicated to …
Didarknet: A contemporary approach to detect and characterize the darknet traffic using deep image learning
Darknet traffic classification is significantly important to categorize real-time applications.
Although there are notable efforts to classify darknet traffic which rely heavily on existing …
Although there are notable efforts to classify darknet traffic which rely heavily on existing …
Analysis of darknet traffic for criminal activities detection using TF-IDF and light gradient boosted machine learning algorithm
Darkweb also called as sinkholes, blackholes, network telescopes, and darknet is the
environment and the most favorable platform for illegal activities due to hidden IP address …
environment and the most favorable platform for illegal activities due to hidden IP address …
Robust stacking ensemble model for darknet traffic classification under adversarial settings
Encrypted traffic tunnelled by Tor or VPN is referred to as darknet traffic. The ability to detect,
identify, and characterize darknet traffic is critical for detecting network traffic generated by a …
identify, and characterize darknet traffic is critical for detecting network traffic generated by a …
Attack-Aware IoT network traffic routing leveraging ensemble learning
Q Abu Al-Haija, A Al-Badawi - Sensors, 2021 - mdpi.com
Network Intrusion Detection Systems (NIDSs) are indispensable defensive tools against
various cyberattacks. Lightweight, multipurpose, and anomaly-based detection NIDSs …
various cyberattacks. Lightweight, multipurpose, and anomaly-based detection NIDSs …
IoT malware network traffic classification using visual representation and deep learning
With the increase of IoT devices and technologies coming into service, Malware has risen as
a challenging threat with increased infection rates and levels of sophistication. Without …
a challenging threat with increased infection rates and levels of sophistication. Without …
DANTD: a deep abnormal network traffic detection model for security of industrial internet of things using high-order features
G Shi, X Shen, F Xiao, Y He - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the development of blockchain, artificial intelligence, and data mining technology,
abnormal network traffic data has become easy to obtain. The traffic detection model detects …
abnormal network traffic data has become easy to obtain. The traffic detection model detects …