Privacy-preserving crowdsourced spectrum sensing

Crowdsourced spectrum sensing has great potential in improving current spectrum database services. Without strong incentives and location privacy protection in place, however, mobile users will be reluctant to act as mobile crowdsourcing workers for spectrum sensing tasks. In this paper, we present PriCSS, the first framework for a crowdsourced spectrum sensing service provider to select spectrum-sensing participants in a differentially privacy-preserving manner. Thorough theoretical analysis and simulation studies show that PriCSS can simultaneously achieve differential location privacy, approximate social cost minimization, and truthfulness.

[1]  Ben Y. Zhao,et al.  Towards commoditized real-time spectrum monitoring , 2014, HotWireless@MobiCom.

[2]  Qian Zhang,et al.  Location Privacy Preservation in Collaborative Spectrum Sensing , 2014 .

[3]  Guihai Chen,et al.  Differentially private spectrum auction with approximate revenue maximization , 2014, MobiHoc '14.

[4]  H. Tullberg,et al.  Sensor Selection for Cooperative Spectrum Sensing , 2008, 2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[5]  Kunal Talwar,et al.  Mechanism Design via Differential Privacy , 2007, 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07).

[6]  Vijay V. Vazirani,et al.  Approximation Algorithms , 2001, Springer Berlin Heidelberg.

[7]  Rui Zhang,et al.  SecureFind: Secure and Privacy-Preserving Object Finding via Mobile Crowdsourcing , 2015, IEEE Transactions on Wireless Communications.

[8]  Chi Zhang,et al.  Secure crowdsourcing-based cooperative pectrum sensing , 2013, 2013 Proceedings IEEE INFOCOM.

[9]  Xinping Guan,et al.  YouSense: Mitigating entropy selfishness in distributed collaborative spectrum sensing , 2013, 2013 Proceedings IEEE INFOCOM.

[10]  Kaigui Bian,et al.  Robust Distributed Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[11]  Kang G. Shin,et al.  Differentially private and strategy-proof spectrum auction with approximate revenue maximization , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[12]  Athanasios V. Vasilakos,et al.  TRAC: Truthful auction for location-aware collaborative sensing in mobile crowdsourcing , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[13]  Daniel A. Spielman,et al.  Spectral Graph Theory and its Applications , 2007, 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07).

[14]  Chi Zhang,et al.  SpecGuard: Spectrum misuse detection in dynamic spectrum access systems , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[15]  Moni Naor,et al.  Our Data, Ourselves: Privacy Via Distributed Noise Generation , 2006, EUROCRYPT.

[16]  Mingyan Liu,et al.  Revenue generation for truthful spectrum auction in dynamic spectrum access , 2009, MobiHoc '09.

[17]  Tim Roughgarden,et al.  Algorithmic Game Theory , 2007 .

[18]  Xi Fang,et al.  Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing , 2012, Mobicom '12.

[19]  Jian Tang,et al.  Truthful incentive mechanisms for crowdsourcing , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[20]  Éva Tardos,et al.  Truthful mechanisms for one-parameter agents , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.

[21]  Rui Zhang,et al.  SafeDSA: Safeguard Dynamic Spectrum Access against Fake Secondary Users , 2015, CCS.

[22]  Zhu Han,et al.  Catch Me if You Can: An Abnormality Detection Approach for Collaborative Spectrum Sensing in Cognitive Radio Networks , 2010, IEEE Transactions on Wireless Communications.

[23]  Tan Zhang,et al.  A vehicle-based measurement framework for enhancing whitespace spectrum databases , 2014, MobiCom.

[24]  Xiang-Yang Li,et al.  How to crowdsource tasks truthfully without sacrificing utility: Online incentive mechanisms with budget constraint , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[25]  Qian Zhang,et al.  Privacy-Preserving Collaborative Spectrum Sensing With Multiple Service Providers , 2015, IEEE Transactions on Wireless Communications.

[26]  Rui Zhang,et al.  PriStream: Privacy-preserving distributed stream monitoring of thresholded PERCENTILE statistics , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[27]  Cynthia Dwork,et al.  Differential Privacy , 2006, ICALP.

[28]  Kaigui Bian,et al.  Blind Transmitter Authentication for Spectrum Security and Enforcement , 2014, CCS.

[29]  Kang G. Shin,et al.  Attack-tolerant distributed sensing for dynamic spectrum access networks , 2009, 2009 17th IEEE International Conference on Network Protocols.

[30]  Wei Cheng,et al.  ARTSense: Anonymous reputation and trust in participatory sensing , 2013, 2013 Proceedings IEEE INFOCOM.

[31]  Peng Ning,et al.  Authenticating Primary Users' Signals in Cognitive Radio Networks via Integrated Cryptographic and Wireless Link Signatures , 2010, 2010 IEEE Symposium on Security and Privacy.

[32]  Cyrus Shahabi,et al.  A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing , 2014, Proc. VLDB Endow..

[33]  Aaron Roth,et al.  Differentially private combinatorial optimization , 2009, SODA '10.

[34]  Sampath Kannan,et al.  The Exponential Mechanism for Social Welfare: Private, Truthful, and Nearly Optimal , 2012, 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science.

[35]  Shuai Li,et al.  Security and privacy of collaborative spectrum sensing in cognitive radio networks , 2012, IEEE Wireless Communications.