NeTS: Small: Collaborative Research: Enhancing Crowdsourced Spectrum Sensing through Sybil-proof Incentives

数据库驱动的动态频谱共享是解决频谱短缺和提高频谱利用率最有希望的方法之一，已被美国联邦通信委员会（Federal Communications Commission）提出。在这种系统中，频谱服务提供商（SSP）接受主用户的注册，并根据用户对频谱的使用情况确定频谱的可用性。有兴趣使用频谱的辅助用户需要联系SSP查询任何感兴趣频段的频谱可用性。利用众包的力量，频谱感知成为有效提高频谱估计精度的关键因素。在众包频谱感知中，SSP将频谱感知任务外包给大量招募的移动用户。然而，许多现有的众包激励机制容易受到Sybil攻击的影响，攻击者非法伪造多个身份以获得利益，但却降低了性能。该项目的目标是通过设计抗sybil激励机制，克服现有激励机制的不足，增强众包频谱感知。该项目将提高人们对群源频谱传感系统中可能发生的西比尔攻击的认识。预期的结果也将在设计基于众包的应用程序的激励机制方面开辟新的领域。这个项目将吸引少数民族学生和代表性不足的群体。拟议的研究活动将通过课程发展和专题讨论会补充和丰富亚利桑那州立大学和科罗拉多矿业学院不断增加的课程。拟议的研究包括两个相互关联的研究重点。推力1专注于通过在直接众包架构下的抗sybill激励机制设计来增强众包频谱感知，其中移动用户直接与SSP通信。在收到感知任务描述后，每个移动用户提出感知计划并请求奖励。SSP选择一组获胜用户，并决定向每个获胜卖家支付相应的款项。获胜的用户执行感知任务并获得相应的奖励。推力2侧重于通过在分层众包架构下的防sybill激励机制设计来增强众包，其中移动用户在频谱感知和征求中都做出了贡献。该模型包含了赢得DARPA网络挑战的方法，但容易受到Sybil攻击。私人银行将设计不受sybil影响的激励机制。所提出的研究将通过模拟和试验台实验进行评估和验证。

Database-driven dynamic spectrum sharing has been advocated by the Federal Communications Commission as one of the most promising methods to address the spectrum shortage and improve the spectrum utilization. In such a system, a spectrum service provider (SSP) accepts registrations from primary users and determines spectrum availability based on their use of spectrum. Secondary users interested in using the spectrum are required to contact the SSP to inquire about spectrum availability in any band of interest. Leveraging the power of crowd-sourcing, spectrum sensing becomes a key enabler for effectively improving the spectrum-estimation accuracy. In crowd-sourced spectrum sensing, an SSP outsources spectrum-sensing tasks to a large number of recruited mobile users. However, many existing incentive mechanisms for crowd-sourcing are vulnerable to Sybil attacks, where an attacker illegitimately forges multiple identities to gain benefits but degrades the performance. The goal of this project is to enhance crowd-sourced spectrum sensing by designing Sybil-proof incentive mechanisms that overcome the shortcomings of current incentive mechanisms. This project will raise awareness about the possible Sybil attacks in crowd-sourced spectrum sensing systems. The anticipated results will also break new grounds in designing incentive mechanisms for crowdsourcing-based applications. This project will engage minority students and under-represented groups. The proposed research activities will complement and enrich the growing curricula at Arizona State University and Colorado School of Mines through course development and special topic seminars.The proposed research consists of two inter-related research thrusts. Thrust 1 concentrates on enhancing crowd-sourced spectrum sensing through Sybil-proof incentive mechanism design under a direct crowd-sourcing architecture, where mobile users communicate directly with the SSP. Upon receiving the sensing task description, each mobile user proposes a sensing plan together with a request for reward. The SSP selects the set of winning users and decides the corresponding payment to each winning seller. The winning users perform the sensing tasks and receive the corresponding rewards. Thrust 2 concentrates on enhancing crowd-sourcing through Sybil-proof incentive mechanism design under a hierarchical crowd-sourcing architecture, where mobile users contribute in both spectrum sensing and solicitation. This model subsumes the approach that won the DARPA networking challenge, but is vulnerable to Sybil attacks. The PIs will design Sybil-proof incentive mechanisms. The proposed research will be evaluated and validated via simulations and testbed experiments.