An intelligent tree-based intrusion detection model for cyber security

M Al-Omari, M Rawashdeh, F Qutaishat… - Journal of Network and …, 2021 - Springer
The widespread use of the Internet of Things and distributed heterogeneous devices has
shed light on the implementation of efficient and reliable intrusion detection systems. These …

Intrusion detection and prevention in networks using machine learning and deep learning approaches: a review

JA Abraham, VR Bindu - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
As network services are used more and more, security is considered one of the main and
important concerns of the network. Many computers connected to the network play important …

Memory-efficient deep learning for botnet attack detection in IoT networks

SI Popoola, B Adebisi, R Ande, M Hammoudeh… - Electronics, 2021 - mdpi.com
Cyber attackers exploit a network of compromised computing devices, known as a botnet, to
attack Internet-of-Things (IoT) networks. Recent research works have recommended the use …

Intrusion detection in internet of things using convolutional neural networks

M Kodyš, Z Lu, KW Fok… - 2021 18th International …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) has become a popular paradigm to fulfil needs of the industry such
as asset tracking, resource monitoring and automation. As security mechanisms are often …

Large-scale urban iot activity data for ddos attack emulation

A Hekmati, E Grippo, B Krishnamachari - Proceedings of the 19th ACM …, 2021 - dl.acm.org
As IoT deployments grow in scale for applications such as smart cities, they face increasing
cyber-security threats. In particular, as evidenced by the famous Mirai incident and other …

[PDF][PDF] A hybrid classification approach for intrusion detection in iot network

S Choudhary, N Kesswani - 2021 - core.ac.uk
With the increase in number of IoT devices, the capabilities to provide reliable security and
detect the malicious activities within the IoT network have become quite challenging. We …

Characterization of IEEE 802.11 communications and detection of low-power jamming attacks in noncontrolled environment based on a clustering study

J Villain, V Deniau, C Gransart, A Fleury… - IEEE Systems …, 2021 - ieeexplore.ieee.org
Wireless connections are more and more used in different applications and in public areas
for services to consumers but also for handling (sometimes) sensitive communications (for …

Dataset: Large-scale urban IoT activity data for DDOS attack emulation

A Hekmati, E Grippo, B Krishnamachari - arXiv preprint arXiv:2110.01842, 2021 - arxiv.org
As IoT deployments grow in scale for applications such as smart cities, they face increasing
cyber-security threats. In particular, as evidenced by the famous Mirai incident and other …

Network Intrusion Detection in the Wild-the Orange use case in the SIMARGL project

M Komisarek, M Pawlicki, M Kowalski… - Proceedings of the 16th …, 2021 - dl.acm.org
There is a profuse abundance of network security incidents around the world every day.
Increasingly, services and data stored on servers fall victim to sophisticated techniques that …

A Protocol-based Intrusion Detection System using Dual Autoencoders

YL Huang, CY Hung, HT Hu - 2021 IEEE 21st International …, 2021 - ieeexplore.ieee.org
This paper proposes a dual Autoencoder-based Intrusion Detection System (duAE-IDS) for
the ever-changing network attacks. duAE-IDS is a protocol-based IDS, which divides traffic …