NeTS: Small: Secure Crowdsourcing-Based Cooperative Spectrum Sensing NeTS: Small: Secure Crowdsourcing-Based Cooperative Spectrum Sensing Project Summary NeTS: Small: Secure Crowdsourcing-Based Cooperative Spectrum Sensing Crowdsourcing-based cooperative spectrum sensing (CCSS) refers to a spectrum-sensing service provider (SSP) outsourcing the spectrum-sensing tasks over a large geographic region to distributed mobile users. These mobile users are called mobile detectors and can perform spectrum sensing via either internal spectrum sensors or external ones provided by the SSP. The feasibility of CCSS is deeply rooted in the ubiquitous penetration of increasingly powerful mobile devices into everyday life and in the an- ticipated prevalence of dynamic spectrum access (DSA) in future mobile communication systems. CCSS is expected to be much more cost-effective than deploying a large-scale dedicated network of distributed spectrum senors, which is notoriously difficult to deploy, operate, and maintain. Releasing the full potential of CCSS faces many technical challenges. First, mobile detectors are nat- urally self-interested and need strong incentives for performing spectrum sensing. Second, mobile users may hesitate to participate in CCSS due to growing concerns about their location privacy. Third, mo- bile detectors may submit false sensing reports to the SSP due to device failures or malicious intention, thus largely affecting the accuracy of channel occupancy inference. Last, there may be illegal spectrum use which would severely interfere with proper spectrum use authorized by the SSP. Although there has been separate attempt to address individual challenges above, it is infeasible to integrate existing solutions into a unified framework due to their diverse and often conflicting assumptions. Intellectual Merit: This proposal outlines a challenging research plan on a secure and privacy-preserving CCSS architecture, under which the above challenges are tackled in a systematic fashion. The proposed research comprises four main tasks: (1) incentive-aware and reputation-aware selection of mobile detectors whereby the SSP can select an optimal set of mobile detectors for a sensing task subject to incentive, cost, spatial diversity, and trust constraints; (2) secure combination which enables the SSP to minimize the impact of false sensing reports on the final detection result; (3) a reputation system which records the past sensing performance of mobile detectors and provides crucial input into the selection of mobile detectors and the secure combination of sensing reports; and (4) spectrum-misuse detection to enable the realtime detection of unauthorized spectrum use. Complementing the above theoretical studies, this project includes a validation component, involv- ing MATLAB and ns-3 simulations, real implementations on smartphones, tablets, laptops, and Univer- sal Software Radio Peripheral platforms, indoor experiments, and outdoor tests based on a functional 4G/LTE research facility on the ASU campus. In addition to strengthening the theoretical research, this validation component will be effectively used as an educational vehicle to involve a broader group of students in this research project. Broader Impact: DSA is the key to solving the national spectrum shortage and implementing the US National Broadband Plan. The scientific promise of the proposed research will expand the fundamental understanding of security, privacy, and incentive issues in CCSS. Successful development of the proposed algorithms and their implementations will have profound impact on fostering the practical use of DSA. A substantial quantity of the materials of this project will be made publicly available online in the forms of tutorials, talks, publications, and software toolkits. An important objective of this project is to develop a cross-disciplinary graduate course on DSA. In addition, the PI aims to enhance undergraduate research experience through the validation component of the project. Moreover, the PI is strongly committed to providing research opportunities to woman and underrepresented students by actively participating in ASUs Minority Engineering program, Women in Science and Engineering program, and Mountain State Alliance. Finally, the PI outreach plan includes active involvement in the ASU engineering outreach/summer programs to foster the interest of K-12 students in the STEM fields as well as half-day tutorials on the project findings at the annual IAB meetings of ASU Sensor Signal and Information Processing Center (an NSF I/UCRC site).
|Effective start/end date||9/1/13 → 8/31/18|
- NSF-CISE: Computer and Network Systems (CNS): $500,000.00
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