Iot traffic-based DDoS attacks detection mechanisms: A comprehensive review
Abstract The Internet of Things (IoT) has emerged as an inevitable part of human life, that
includes online learning, smart homes, smart cars, smart grids, smart cities, agriculture, and …
includes online learning, smart homes, smart cars, smart grids, smart cities, agriculture, and …
Efficient intelligent intrusion detection system for heterogeneous Internet of Things (HetIoT)
Moving towards a more digital and intelligent world equipped with internet-of-thing (IoT)
devices creates many security issues. A distributed denial of service (DDoS) attack is one of …
devices creates many security issues. A distributed denial of service (DDoS) attack is one of …
Hybrid machine learning model for efficient botnet attack detection in iot environment
Cyber attacks are growing with the rapid development and wide use of internet technology.
Botnet attack emerged as one of the most harmful attacks. Botnet identification is becoming …
Botnet attack emerged as one of the most harmful attacks. Botnet identification is becoming …
Flow-mae: Leveraging masked autoencoder for accurate, efficient and robust malicious traffic classification
Z Hang, Y Lu, Y Wang, Y **e - … of the 26th International Symposium on …, 2023 - dl.acm.org
Malicious traffic classification is crucial for Intrusion Detection Systems (IDS). However,
traditional Machine Learning approaches necessitate expert knowledge and a significant …
traditional Machine Learning approaches necessitate expert knowledge and a significant …
[HTML][HTML] Comprehensive Botnet Detection by Mitigating Adversarial Attacks, Navigating the Subtleties of Perturbation Distances and Fortifying Predictions with …
Botnets are computer networks controlled by malicious actors that present significant
cybersecurity challenges. They autonomously infect, propagate, and coordinate to conduct …
cybersecurity challenges. They autonomously infect, propagate, and coordinate to conduct …
An intrusion detection system using extended Kalman filter and neural networks for IoT networks
DD Kulkarni, RK Jaiswal - Journal of Network and Systems Management, 2023 - Springer
The unparalleled growth of the Internet of Things (IoT) is introducing a new paradigm shift in
networking technology. By connecting everyday devices to the internet and enabling them to …
networking technology. By connecting everyday devices to the internet and enabling them to …
PeerG: A P2P botnet detection method based on representation learning and graph contrastive learning
G Wu, X Wang, J Zhang - Computers & Security, 2024 - Elsevier
P2P botnets are distributed with complex topology and communication behavior, making
them harder to detect and remove. Individuals or organizations can effectively detect P2P …
them harder to detect and remove. Individuals or organizations can effectively detect P2P …
A Malicious Botnet Traffic Detection Using Machine Learning.
M Sakthivel, S Sivanantham… - Journal of …, 2022 - search.ebscohost.com
Detection of incorrect and malign data transfers in the Internet of Things (IoT) network is
important for IoT safety to observe an eye on and prevent unwelcomed traffic flow to the …
important for IoT safety to observe an eye on and prevent unwelcomed traffic flow to the …
[HTML][HTML] Lurking in the shadows: Unsupervised decoding of beaconing communication for enhanced cyber threat hunting
The escalating prevalence of Advanced Persistent Threats (APTs) necessitates the
development of more robust solutions capable of effectively thwarting these attacks by …
development of more robust solutions capable of effectively thwarting these attacks by …
Toward Generating Communication Graph Datasets for Botnet Detection in Autonomous Systems
Botnet is one of the main threats to cybersecurity because of its concealment and hazardous
nature, especially in autonomous systems (ASs), such as campus networks. Graph-based …
nature, especially in autonomous systems (ASs), such as campus networks. Graph-based …