Rdtids: Rules and decision tree-based intrusion detection system for internet-of-things networks
This paper proposes a novel intrusion detection system (IDS), named RDTIDS, for Internet-of-
Things (IoT) networks. The RDTIDS combines different classifier approaches which are …
Things (IoT) networks. The RDTIDS combines different classifier approaches which are …
An anomaly detection model for IoT networks based on flow and flag features using a feed-forward neural network
I Ullah, QH Mahmoud - 2022 IEEE 19th Annual Consumer …, 2022 - ieeexplore.ieee.org
The security of IoT networks is becoming increasingly challenging, and anomaly detection
for IoT network traffic is a critical technique for addressing this issue. However, extracting …
for IoT network traffic is a critical technique for addressing this issue. However, extracting …
Network intrusion detection for IoT security based on learning techniques
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
LITNET-2020: An annotated real-world network flow dataset for network intrusion detection
Network intrusion detection is one of the main problems in ensuring the security of modern
computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In …
computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In …
[HTML][HTML] A machine learning-based intrusion detection for detecting internet of things network attacks
Abstract The Internet of Things (IoT) refers to the collection of all those devices that could
connect to the Internet to collect and share data. The introduction of varied devices …
connect to the Internet to collect and share data. The introduction of varied devices …
MAGRU-IDS: A multi-head attention-based gated recurrent unit for intrusion detection in IIoT networks
The increasing prevalence of the Industrial Internet of Things (IIoT) in industrial
environments amplifies the potential for security breaches and compromises. To monitor IIoT …
environments amplifies the potential for security breaches and compromises. To monitor IIoT …
Top-down machine learning-based architecture for cyberattacks identification and classification in IoT communication networks
Q Abu Al-Haija - Frontiers in big Data, 2022 - frontiersin.org
With the prompt revolution and emergence of smart, self-reliant, and low-power devices,
Internet of Things (IoT) has inconceivably expanded and impacted almost every real-life …
Internet of Things (IoT) has inconceivably expanded and impacted almost every real-life …
RETRACTED ARTICLE: FSO-LSTM IDS: hybrid optimized and ensembled deep-learning network-based intrusion detection system for smart networks
AS Alqahtani - The Journal of Supercomputing, 2022 - Springer
Abstract The Internet of Things (IoT) has achieved exponential growth worldwide. Although
the IoT is used by millions of users, these networks are handicapped by attacks such as …
the IoT is used by millions of users, these networks are handicapped by attacks such as …
An IoT-focused intrusion detection system approach based on preprocessing characterization for cybersecurity datasets
Security in IoT networks is currently mandatory, due to the high amount of data that has to be
handled. These systems are vulnerable to several cybersecurity attacks, which are …
handled. These systems are vulnerable to several cybersecurity attacks, which are …
A lightweight supervised intrusion detection mechanism for IoT networks
S Roy, J Li, BJ Choi, Y Bai - Future Generation Computer Systems, 2022 - Elsevier
Abstract As the Internet of Things (IoT) is becoming increasingly popular, we have
experienced more security breaches that are associated with the connection of vulnerable …
experienced more security breaches that are associated with the connection of vulnerable …