Trust based Fusion over Noisy Channels through Anomaly Detection in Cognitive Radio Networks
Abstract
Byzantine attacks have been identified as one of the key vulnerabilities in cognitive radio networks, where malicious nodes advertise false spectrum occupancy data in a cooperative environment. In such cases, the resultant fused data is very different from the actual scenario. Thus, there is a need to identify the malicious nodes or at least find the trustworthiness of nodes such that the data sent by malicious nodes could be filtered out. The process is complicated by presence of noise in the channel which makes it harder to distinguish anomalies caused by malicious activity and those caused due to unreliable noisy channels.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2011
- Accession Number
- ADA560910
Entities
People
- Kevin Kwait
- Mainak Chatterjee
- Saptarshi Debroy
- Shameek Bhattacharjee
Organizations
- University of Central Florida