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无线网络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传输和接收数据，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，恶意软件可能会导致SDR在用户不知情的情况下显示非法频谱使用。联邦通信委员会有一个执法局，通过投诉和广泛的人工调查来检测干扰。目前用于定位频谱违规者的机制耗时、人力密集且昂贵。违规者的非法频谱使用可能过于临时或过于移动，无法使用现有流程检测和定位。该项目设想了这样一个未来：部署在家庭、社区和办公楼、车辆和手机上的众包和网络化频谱传感器舰队将检测、识别和定位跨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保护隐私的众包方法，以检测和定位频谱违规者。新工具可以快速找到违法者，这将阻止用户进行非法SDR活动，并能从侵犯频谱的恶意软件中恢复。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有效、可靠和公平地使用频谱。将针对无线通信、动态频谱接入、数据挖掘、网络安全和众包等主题开发用于公共宣传的新课程材料和演示。在寻找频谱违规者的方法和工具的开发方面，该项目将解决几个挑战。首先，该项目将通过不解码传输数据的众包频谱测量实现罪犯的本地化，从而保护用户的数据和身份隐私。其次，众包传感策略将隐式适应交通密度，显式适应关注可疑活动。接下来，传感策略将保持在能源预算范围内，并具有激励模型以鼓励参与，同时具有足够的空间和时间覆盖范围，以便在检测非法活动方面提供高统计可信度。最后，将使用模拟和广泛的实验对开发的方法进行评估，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.