# Differential Privacy in Cognitive Radio Networks: A Comprehensive Survey

arXiv: https://arxiv.org/abs/2111.02011 · HTML: https://mlsanity.com/paper/2111.02011/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2021.

## Built on by (most cited first, 2 of 2)

- [Deep Learning Frameworks for Cognitive Radio Networks: Review and Open Research Challenges](https://mlsanity.com/paper/2410.23949/) (2024)
- [Contextualize differential privacy in image database: a lightweight image differential privacy approach based on principle component analysis inverse](https://mlsanity.com/paper/2202.08309/) (2022)

## Abstract (arXiv)

Background/Introduction: Integrating cognitive radio (CR) with traditional wireless networks is helping solve the problem of spectrum scarcity in an efficient manner. The opportunistic and dynamic spectrum access features of CR provide the functionality to its unlicensed users to utilize the underutilized spectrum at the time of need because CR nodes can sense vacant bands of spectrum and can also access them to carry out communication. Various capabilities of CR nodes depend upon efficient and continuous reporting of data with each other and centralized base stations, which in turn can cause leakage in privacy. Experimental studies have shown that the privacy of CR users can be compromised easily during the cognition cycle, because they are knowingly or unknowingly sharing various personally identifiable information (PII), such as location, device ID, signal status, etc. In order to preserve this privacy leakage, various privacy preserving strategies have been developed by researchers, and according to us differential privacy is the most significant among them.