[PDF][PDF] Designing an effective network forensic framework for the investigation of botnets in the Internet of Things
N Koroniotis - 2020 - unsworks.unsw.edu.au
In recent times, the world has come to rely greatly on the Internet and the services that it
provides. As such, it should come as no surprise that innovations that harness the …
provides. As such, it should come as no surprise that innovations that harness the …
IoT network attack detection and mitigation
Cyberattacks on the Internet of Things (IoT) can cause major economic and physical
damage, and disrupt production lines, manufacturing processes, supply chains, impact the …
damage, and disrupt production lines, manufacturing processes, supply chains, impact the …
[PDF][PDF] Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm.
AHB Aighuraibawi, S Manickam, R Abdullah… - Comput. Syst. Sci …, 2023 - researchgate.net
Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4× 1038 unique
IP addresses of devices in the network. IPv6 has introduced new features like Neighbour …
IP addresses of devices in the network. IPv6 has introduced new features like Neighbour …
Ensemble classification using traffic flow metrics to predict distributed denial of service scope in the Internet of Things (IoT) networks
K Rambabu, N Venkatram - Computers & Electrical Engineering, 2021 - Elsevier
The IoT networks are highly vulnerable to distributed denial of service, which is the most
serious and intolerable attack format. The competent solutions to handle DDOS attacks on …
serious and intolerable attack format. The competent solutions to handle DDOS attacks on …
Random neural network for lightweight attack detection in the iot
Cyber-attack detection has become a basic component of all information processing
systems, and once an attack is detected it may be possible to block or mitigate its effects …
systems, and once an attack is detected it may be possible to block or mitigate its effects …
Simulation and modeling for anomaly detection in IoT network using machine learning
Today we are living in an era where everything is changing to be smart, whether it be a
smart home, smart industries, smart irrigation, or a smart meter, where the word smart refers …
smart home, smart industries, smart irrigation, or a smart meter, where the word smart refers …
Botnet attack detection with incremental online learning
In recent years, IoT devices have often been the target of Mirai Botnet attacks. This paper
develops an intrusion detection method based on Auto-Associated Dense Random Neural …
develops an intrusion detection method based on Auto-Associated Dense Random Neural …
Online self-supervised learning in machine learning intrusion detection for the internet of things
This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which
enables a fully online Machine Learning (ML) based Intrusion Detection System (IDS) that …
enables a fully online Machine Learning (ML) based Intrusion Detection System (IDS) that …
G-networks can detect different types of cyberattacks
Malicious network attacks are a serious source of concern, and machine learning
techniques are widely used to build Attack Detectors with off-line training with real attack and …
techniques are widely used to build Attack Detectors with off-line training with real attack and …
[PDF][PDF] Mitigating the impact of IoT routing attacks on power consumption in IoT healthcare environment using convolutional neural network
SOM Kamel, SA Elhamayed - International Journal of Computer …, 2020 - researchgate.net
IoT provides big contribution to healthcare for elderly care at home. There are many attacks
in IoT healthcare network which may destroy the entire network. A propose a framework may …
in IoT healthcare network which may destroy the entire network. A propose a framework may …