Attack Modeling and Security Analysis Using Machine Learning Algorithms Enabled with Augmented Reality and Virtual Reality
Автор: Momina Mushtaq, Rakesh Kumar Jha, Manish C. Sabraj, Shubha Jain
Журнал: International Journal of Computer Network and Information Security @ijcnis
Статья в выпуске: 4 vol.16, 2024 года.
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Augmented Reality (AR) and Virtual Reality (VR) are innovative technologies that are experiencing a widespread recognition. These technologies possess the capability to transform and redefine our interactions with the surrounding environment. However, as these technologies spread, they also introduce new security challenges. In this paper, we discuss the security challenges posed by Augmented reality and Virtual Reality, and propose a Machine Learning-based approach to address these challenges. We also discuss how Machine Learning can be used to detect and prevent attacks in Augmented reality and Virtual Reality. By leveraging the power of Machine Learning algorithms, we aim to bolster the security defences of Augmented reality and Virtual Reality systems. To accomplish this, we have conducted a comprehensive evaluation of various Machine Learning algorithms, meticulously analysing their performance and efficacy in enhancing security. Our results show that Machine Learning can be an effective way to improve the security of Augmented reality and virtual reality systems.
Algorithms, Augmented Reality (AR), Machine Learning, Security, Virtual Reality (VR)
Короткий адрес: https://sciup.org/15019299
IDR: 15019299 | DOI: 10.5815/ijcnis.2024.04.08
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