A Novel Attack Detection Technique to Protect AR-Based IoT Devices from DDoS Attacks

Kwok Tai Chui; Varsha Arya; Dragan Peraković; Wadee Alhalabi

doi:10.1007/978-3-031-22018-0_34

A Novel Attack Detection Technique to Protect AR-Based IoT Devices from DDoS Attacks

Kwok Tai Chui, Varsha Arya, Dragan Peraković, Wadee Alhalabi

Electronic Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Argumented reality (AR) has become increasingly important tools for transferring data between machines and people as a result of advances in smart gadgets and artificial intelligence (AI). Traditional rigid sensors have outpaced flexible and IoT devices that can be easily incorporated into AR systems. In recent years, adaptable IoT-based AR have been extensively studied for smart skins in the areas of physiological monitoring, motion detection, robotics, healthcare, and other applications. Researchers are focusing on developing the idea of AI in all domains. There are, of course, certain limits to AR ideas and concepts at this stage in their development. To protect AR enabled smart devices from various types of cyber threat, it is necessary to provide security and authentication mechanisms. In this context, in this paper we present a novel attack detection technology that is used to detect DDoS attacks AR-based IoT devices. The proposed approach detects malicious operations with an accuracy of 92.84%. Also works efficiently as compared to other machine learning techniques.

Original language	English
Title of host publication	International Conference on Cyber Security, Privacy and Networking, ICSPN 2022
Editors	Nadia Nedjah, Gregorio Martínez Pérez, B.B. Gupta
Pages	361-373
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-031-22018-0_34
Publication status	Published - 2023
Event	International Conference on Cyber Security, Privacy and Networking, ICSPN 2022 - Virtual, Online Duration: 9 Sept 2021 → 11 Sept 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	599 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Cyber Security, Privacy and Networking, ICSPN 2022
City	Virtual, Online
Period	9/09/21 → 11/09/21

Keywords

Augmented reality
DDoS
Edge computing
IoT
Mixed reality
Smart devices
Virtual reality

Access to Document

10.1007/978-3-031-22018-0_34

Cite this

Chui, K. T., Arya, V., Peraković, D., & Alhalabi, W. (2023). A Novel Attack Detection Technique to Protect AR-Based IoT Devices from DDoS Attacks. In N. Nedjah, G. Martínez Pérez, & B. B. Gupta (Eds.), International Conference on Cyber Security, Privacy and Networking, ICSPN 2022 (pp. 361-373). (Lecture Notes in Networks and Systems; Vol. 599 LNNS). https://doi.org/10.1007/978-3-031-22018-0_34

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abstract = "Argumented reality (AR) has become increasingly important tools for transferring data between machines and people as a result of advances in smart gadgets and artificial intelligence (AI). Traditional rigid sensors have outpaced flexible and IoT devices that can be easily incorporated into AR systems. In recent years, adaptable IoT-based AR have been extensively studied for smart skins in the areas of physiological monitoring, motion detection, robotics, healthcare, and other applications. Researchers are focusing on developing the idea of AI in all domains. There are, of course, certain limits to AR ideas and concepts at this stage in their development. To protect AR enabled smart devices from various types of cyber threat, it is necessary to provide security and authentication mechanisms. In this context, in this paper we present a novel attack detection technology that is used to detect DDoS attacks AR-based IoT devices. The proposed approach detects malicious operations with an accuracy of 92.84%. Also works efficiently as compared to other machine learning techniques.",

keywords = "Augmented reality, DDoS, Edge computing, IoT, Mixed reality, Smart devices, Virtual reality",

author = "Chui, {Kwok Tai} and Varsha Arya and Dragan Perakovi{\'c} and Wadee Alhalabi",

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Chui, KT, Arya, V, Peraković, D & Alhalabi, W 2023, A Novel Attack Detection Technique to Protect AR-Based IoT Devices from DDoS Attacks. in N Nedjah, G Martínez Pérez & BB Gupta (eds), International Conference on Cyber Security, Privacy and Networking, ICSPN 2022. Lecture Notes in Networks and Systems, vol. 599 LNNS, pp. 361-373, International Conference on Cyber Security, Privacy and Networking, ICSPN 2022, Virtual, Online, 9/09/21. https://doi.org/10.1007/978-3-031-22018-0_34

A Novel Attack Detection Technique to Protect AR-Based IoT Devices from DDoS Attacks. / Chui, Kwok Tai; Arya, Varsha; Peraković, Dragan et al.
International Conference on Cyber Security, Privacy and Networking, ICSPN 2022. ed. / Nadia Nedjah; Gregorio Martínez Pérez; B.B. Gupta. 2023. p. 361-373 (Lecture Notes in Networks and Systems; Vol. 599 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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