Abstract
The scientific community is transitioning toward sixth-generation (6G) technology, with a focus on meeting the escalating requirement for secure wireless connectivity amidst the surge in wireless data traffic and the need for low-latency communication. The notion of reconfigurable intelligent surfaces (RIS) emerges as a solution to mitigate security vulnerabilities by intelligently manipulating wireless channel conditions, thus presenting a promising avenue for 6G wireless communication. Delving into the applications of RIS within the context of 6G, various configurations of RIS-assisted wireless systems are scrutinized, covering diverse scenarios, system and fading models, as well as performance metrics and objectives, in a comprehensive and methodical manner.
| Original language | English |
|---|---|
| Title of host publication | Split Federated Learning for Secure IoT Applications |
| Subtitle of host publication | Concepts, frameworks, applications and case studies |
| Publisher | Institution of Engineering and Technology |
| Pages | 79-94 |
| Number of pages | 16 |
| ISBN (Electronic) | 9781839539466 |
| ISBN (Print) | 9781839539459 |
| DOIs | |
| Publication status | Published - 01-01-2024 |
All Science Journal Classification (ASJC) codes
- General Computer Science