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A Lean and Modular Two-Stage Network Intrusion Detection System for IoT Traffic

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Author(s):
Inacio, Bruno Brandao ; Carvalho de Araujo, Juliana C. ; dos Santos, Aldri L. ; Nogueira, Michele ; Hirata, R., Jr. ; Batista, Daniel M.
Total Authors: 6
Document type: Journal article
Source: 2024 IEEE LATIN-AMERICAN CONFERENCE ON COMMUNICATIONS, LATINCOM; v. N/A, p. 6-pg., 2024-01-01.
Abstract

The popularization of the Internet of Things (IoT) has led to cyberattacks targeting interconnected applications. Traditional intrusion detection systems (IDS) struggle to cope with the increasing volume and complexity of IoT data, hindering their ability to identify all threats. In order to address this issue, we propose a modular two-stage Network IDS for IoT, with each stage specialized in a specific set of attacks. This approach allows for independent training and optimization of each stage, improving processing time and classification metrics when compared to single-stage systems. The effectiveness of this design is demonstrated using the CICIoT2023 dataset. Compared to a single model, our proposal obtains better inference time (13 seconds vs. 94 seconds) and an overall enhanced detection rate (0.9055 vs. 0.8370 in terms of F1-Score). An additional contribution of our work is the sharing of all developed code as open-source software, facilitating the reproduction and extension of our proposal. (AU)

FAPESP's process: 18/23098-0 - MENTORED: from modeling to experimentation - predicting and detecting DDoS and zero-day attacks
Grantee:Michele Nogueira Lima
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 22/15304-4 - Learning context rich representations for computer vision
Grantee:Nina Sumiko Tomita Hirata
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 15/24485-9 - Future internet for smart cities
Grantee:Fabio Kon
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 14/50937-1 - INCT 2014: on the Internet of the Future
Grantee:Fabio Kon
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 21/06995-0 - Starling: security and resource allocation on B5G via artificial intelligence techniques
Grantee:Daniel Macêdo Batista
Support Opportunities: Regular Research Grants