NeTS: Medium: Collaborative Research: Detecting and Localizing Spectrum Offenders Using Crowdsourcing

软件定义无线电（SDR）正在成为满足国家移动的无线网络上快速增长的数据速率需求同时确保与其他频谱用户共存的关键技术。 当SDR在普通人手中和口袋里时，自私的用户很容易改变他的设备，在未经授权的频谱上发送和接收数据，或者忽略优先级规则，使网络对许多其他用户来说不那么可靠。 此外，恶意软件可能导致SDR在用户不知情的情况下表现出非法频谱使用。 公平竞争委员会设有一个执法局，通过投诉和广泛的人工调查发现干扰。目前用于定位频谱违规者的机制是耗时的、人力密集的和昂贵的。 违规者的非法频谱使用可能太临时或太移动的而无法使用现有过程检测和定位。 该项目设想了一个未来，在家庭，社区和办公楼，车辆和手机中部署的众包和网络化频谱传感器将检测，识别和定位广泛区域和频段的频谱非法使用。该项目将调查和测试新的隐私保护众包方法，以检测和定位频谱违规者。 快速发现违规者的新工具将阻止用户进行非法SDR活动，并使其能够从频谱违规恶意软件中恢复。 简而言之，这些工具将确保网络运营商、政府和科学目的以及无线用户高效、可靠和公平地使用频谱。 将开发新的课程材料和演示，供公众宣传使用，主题包括无线通信、动态频谱接入、数据挖掘、网络安全和众包。在开发查找频谱犯罪者的方法和工具方面，该项目将应对若干挑战。 首先，该项目将通过众包频谱测量实现罪犯的本地化，这些测量不会解码传输的数据，从而保护用户？数据和身份隐私。 其次，众包传感策略将隐式地适应交通密度，并显式地适应于关注可疑活动。 接下来，感测策略将保持在能量预算内，并且具有鼓励参与的激励模型，但具有足够的空间和时间覆盖范围，以在检测非法活动时提供高统计置信度。 最后，将使用模拟和广泛的实验来评估所开发的方法，以量化性能并为其他研究人员提供丰富的公共数据集。

Software defined radio (SDR) is emerging as a key technology to satisfy rapidly increasing data rate demands on the nation's mobile wireless networks while ensuring coexistence with other spectrum users. When SDRs are in the hands and pockets of average people, it will be easy for a selfish user to alter his device to transmit and receive data on unauthorized spectrum, or ignore priority rules, making the network less reliable for many other users. Further, malware could cause an SDR to exhibit illegal spectrum use without the user's awareness. The FCC has an enforcement bureau which detects interference via complaints and extensive manual investigation. The mechanisms used currently for locating spectrum offenders are time consuming, human-intensive, and expensive. A violator's illegal spectrum use can be too temporary or too mobile to be detected and located using existing processes. This project envisions a future where a crowdsourced and networked fleet of spectrum sensors deployed in homes, community and office buildings, on vehicles, and in cell phones will detect, identify, and locate illegal use of the spectrum across a wide areas and frequency bands. This project will investigate and test new privacy-preserving crowdsourcing methods to detect and locate spectrum offenders. New tools to quickly find offenders will discourage users from illegal SDR activity, and enable recovery from spectrum-offending malware. In short, these tools will ensure the efficient, reliable, and fair use of the spectrum for network operators, government and scientific purposes, and wireless users. New course materials and demonstrations for use in public outreach will be developed on the topics of wireless communications, dynamic spectrum access, data mining, network security, and crowdsourcing.There are several challenges the project will address in the development of methods and tools to find spectrum offenders. First, the project will enable localization of offenders via crowdsourced spectrum measurements that do not decode the transmitted data and thus preserve users? data and identity privacy. Second, the crowd-sourced sensing strategy will implicitly adapt to the density of traffic and explicitly adapt to focus on suspicious activity. Next, the sensing strategy will stay within an energy budget, and have incentive models to encourage participation, yet have sufficient spatial and temporal coverage to provide high statistical confidence in detecting illegal activity. Finally, the developed methods will be evaluated using both simulation and extensive experiments, to quantify performance and provide a rich public data set for other researchers.