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Security for the Metaverse: Blockchain and Machine Learning Techniques for Intrusion Detection
  • Vu Truong ,
  • Long Bao Le
Vu Truong
INRS

Corresponding Author:[email protected]

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Long Bao Le
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Abstract

The Metaverse, which is emerging as the next-generation (NextG) Internet, offers an immersive 3D virtual world in which people can organize various virtual activities and interact with each other seamlessly through digital avatars. As the NextG Internet, however, the Metaverse also faces severe security risks inherited from its predecessor as well as various new emerging threats. Furthermore, the decentralized nature of the Metaverse even makes it more challenging to mitigate these issues in a large-scale setting with numerous interactive wearable devices such as augmented, virtual reality (AR/VR) headsets and haptic devices. In this article, we aim to analyze the security aspect of the Metaverse thoroughly with special discussions of solutions enabled by blockchain and machine learning (ML). Firstly, we present a 4-layer architecture of the Metaverse and discuss potential solutions for Metaverse security based on blockchain and ML. Next, we develop a decentralized collaborative intrusion detection system (CIDS) based on blockchain and federated learning (FL) that allows such the Metaverse users to collaboratively protect this digital world, thereby solving the scalability and single-point-of-failure (SPoF) issues of traditional security approaches, which may not be effective in protecting the Metaverse with increasingly sophisticated attacks. Finally, we outline some key challenges and discuss future research directions for Metaverse security.