Neural network-based distributed denial of service (DDoS) attack detection in smart home networks

Book chapter


Ahamad, I, Ahmad, F, Palade, V and Ahamed, A. 2022. Neural network-based distributed denial of service (DDoS) attack detection in smart home networks. in: 6th Smart Cities Symposium (SCS 2022) IEEE.
AuthorsAhamad, I, Ahmad, F, Palade, V and Ahamed, A.
Abstract

Due to various limitations, such as limited power supply, the
lack of storage capability and processing power, Internet of
Things-based smart home networks have become vulnerable to
various cyber-security attacks including Distributed Denial of Service (DDoS) attacks. These attacks are a malicious
attempt to exhaust and overwhelm the target system
resources, which has significant impact on the operation of
smart home net- works. This paper proposes a novel, efficient
and lightweight DDoS attack detection scheme in smart home
networks, which employs artificial neural networks (ANN) to
classify smart home networks traffic into DDoS attacks or
normal traffic. The proposed solution is evaluated on four
datasets, namely, IoT-23, DS2OS, NUSW-NB15GT and CICDDOS2019. Experiments were conducted on two types of
ANN models, i.e., Multilayered Perceptron (MLP) and LongShort-Term Memory (LSTM), which achieved 99.78% and
99.98% accuracy, respectively.

KeywordsInternet of Things (IoT); Distributed Denial of Service (DDoS) attacks; Machine Learning (ML); Deep learning (DL); Smart Home Networks.
Year2022
Book title6th Smart Cities Symposium (SCS 2022)
PublisherIEEE
Output statusPublished
ISBN9781839538544
Publication dates
Online29 May 2023
Publication process dates
Deposited12 Aug 2024
Digital Object Identifier (DOI)https://doi.org/10.1049/icp.2023.0394
Official URLhttps://engx.theiet.org/b/blogs/posts/6th-iet-smart-cities-symposium
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Event6th IET International Smart Cities Symposium, 6th SCS-2022
Web address (URL) of conference proceedingshttps://ieeexplore.ieee.org/xpl/conhome/10137433/proceeding
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