Rogue Access Points Detection Based on Theory of Semi-Supervised Learning
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-72395-2_4
Reference16 articles.
1. Alotaibi, B., Elleithy, K.: An empirical fingerprint framework to detect Rogue Access Points. In: 2015 Long Island Systems, Applications and Technology, Farmingdale, NY, pp. 1–7 (2015). https://doi.org/10.1109/LISAT.2015.7160206
2. Jana, S., Kasera, S.K.: On fast and accurate detection of unauthorized wireless access points using clock skews. IEEE Trans. Mob. Comput. 9(3), 449–462 (2010)
3. Han, H., Sheng, B., Tan, C.C., Li, Q., Lu, S.: A timing-based scheme for rogue AP detection. IEEE Trans. Parallel Distrib. Syst. 22(11), 1912–1925 (2011). https://doi.org/10.1109/TPDS.2011.125
4. Lanze, F., Panchenko, A., Braatz, B., et al.: Letting the puss in boots sweat: detecting fake access points using dependency of clock skews on temperature. In: Proceedings of the 9th ACM Symposium on Information, Computer and Communications Security, pp. 3–14. ACM (2014)
5. Nikbakhsh, S., Manaf, A., Zamani, M., Janbeglou, M.: A novel approach for rogue access point detection on the client side. In: International Conference on Advanced Information Networking and Applications Workshops (2012)
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