M. Carney, Angry LA residents are trying to sabotage Waze data to stop side-street congestion (2014), https://pando.comangry-la-residents-try-to-sabotage-waze-data-to-stop-side\ -street-congestion, 2014.

S. H. Chang and Z. R. Chen, Protecting Mobile Crowd Sensing against Sybil Attacks Using Cloud Based Trust Management System, Mobile Information Systems, vol.30, p.10, 2016.
DOI : 10.1109/MIC.2010.86
URL : http://downloads.hindawi.com/journals/misy/2016/6506341.pdf

A. Chinchore, F. Jiang, and G. Xu, Intelligent sybil attack detection on abnormal connectivity behavior in mobile social networks Knowledge Management in Organizations, pp.602-617, 2015.

G. Danezis and P. Mittal, SybilInfer: Detecting Sybil Nodes using Social Networks, 2009.

R. Dobrescu and F. Ionescu, Large Scale Networks: Modeling and Simulation, 2016.
DOI : 10.1201/9781315368368

J. R. Douceur, The Sybil Attack, Revised Papers from the First International Workshop on Peer-to-Peer Systems. pp. 251?260. IPTPS '01, 2002.
DOI : 10.1007/3-540-45748-8_24

X. Feng, C. Y. Li, D. X. Chen, and J. Tang, A method for defensing against multisource sybil attacks in vanet. Peer-to-Peer Networking and Applications, pp.305-314, 2017.
DOI : 10.1007/s12083-016-0431-x
URL : https://link.springer.com/content/pdf/10.1007%2Fs12083-016-0431-x.pdf

M. Fire, R. Goldschmidt, and Y. Elovici, Online Social Networks: Threats and Solutions, IEEE Communications Surveys & Tutorials, vol.16, issue.4, pp.2019-2036, 2014.
DOI : 10.1109/COMST.2014.2321628
URL : https://doi.org/10.1109/comst.2014.2321628

E. J. Friedman, P. Resnick, and V. Goel, The Social Cost of Cheap Pseudonyms, Maps that live and breathe with data, pp.173-199, 2001.
DOI : 10.1162/105864001300122476

P. Gu, R. Khatoun, Y. Begriche, and A. Serhrouchni, Vehicle Driving Pattern Based Sybil Attack Detection, 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pp.1282-1288, 2016.
DOI : 10.1109/HPCC-SmartCity-DSS.2016.0182

P. Gu, R. Khatoun, Y. Begriche, and A. Serhrouchni, Support Vector Machine (SVM) Based Sybil Attack Detection in Vehicular Networks, 2017 IEEE Wireless Communications and Networking Conference (WCNC), pp.2017-2018, 2017.
DOI : 10.1109/WCNC.2017.7925783

M. B. Sinai, N. Partush, S. Yadid, and E. Yahav, Exploiting Social Navigation, 2014.

W. Wei, F. Xu, C. Tan, and Q. Li, SybilDefender: Defend against sybil attacks in large social networks, 2012 Proceedings IEEE INFOCOM, pp.1951-1959, 2012.
DOI : 10.1109/INFCOM.2012.6195572

Z. Xu, B. Chen, X. Meng, and L. Liu, Towards efficient detection of sybil attacks in location-based social networks, 2017 IEEE Symposium Series on Computational Intelligence (SSCI), pp.2017-2018, 2017.
DOI : 10.1109/SSCI.2017.8285447

H. Yu, M. Kaminsky, P. B. Gibbons, and A. Flaxman, Sybilguard: Defending against sybil attacks via social networks, ACM SIGCOMM '06, pp.267-278, 2006.
DOI : 10.1109/tnet.2008.923723
URL : http://cs.baylor.edu/~donahoo/classes/5321/papers/YKG+06.pdf

X. Zhang, H. Zheng, X. Li, S. Du, and H. Zhu, You are where you have been: Sybil detection via geo-location analysis in OSNs, 2014 IEEE Global Communications Conference, pp.698-703, 2014.
DOI : 10.1109/GLOCOM.2014.7036889