YouSense: Mitigating Entropy Selfishness in Distributed Collaborative Spectrum Sensing
Shuai Li, Haojin Zhu, Zhaoyu Gao, Xinping Guan, Kai Xing

TL;DR
This paper introduces YouSense, a cryptographic-based incentive scheme that effectively isolates entropy selfish users in distributed collaborative spectrum sensing, enhancing sensing performance without complex detection methods.
Contribution
We propose YouSense, a novel OTP-based incentive mechanism that prevents entropy selfishness in spectrum sensing without requiring explicit selfish node detection.
Findings
YouSense successfully isolates entropy selfish users in USRP experiments.
The scheme achieves low system overhead while improving sensing reliability.
It extends to enhance recovery rates by reducing pad set size.
Abstract
Collaborative spectrum sensing has been recognized as a promising approach to improve the sensing performance via exploiting the spatial diversity of the secondary users. In this study, a new selfishness issue is identified, that selfish users sense no spectrum in collaborative sensing. For easier presentation, it's denoted as entropy selfishness. This selfish behavior is difficult to distinguish, making existing detection based incentive schemes fail to work. To thwart entropy selfishness in distributed collaborative sensing, we propose YouSense, a One-Time Pad (OTP) based incentive design that could naturally isolate entropy selfish users from the honest users without selfish node detection. The basic idea of YouSense is to construct a trapdoor one-time pad for each sensing report by combining the original report and a random key. Such a one-time pad based encryption could prevent…
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Taxonomy
TopicsCognitive Radio Networks and Spectrum Sensing · Distributed Sensor Networks and Detection Algorithms · Indoor and Outdoor Localization Technologies
