Abstract
With the popularity of mobile computing, WiFi has become one of the essential technologies for people to access the Internet, and WiFi security has also become a major threat for mobile computing. The Evil-Twin attack can steal a large amount of private data by forging the same SSID as the real Access Point. This paper proposes a passive Evil-Twin attack detection scheme through CSI in physical layer. First of all, we propose a location model based on the edge of landmark area. In this model, the improved MUSIC algorithm is used to calculate each AP’s AoA by CSI phase. Secondly, it proposes an algorithm for simplifying the generation of location model files, which is the dataset of a small number of AoA and RSSI samples. Finally, according to location model, attack detection algorithm combines a large number of crowd sensing data to determine whether it is a malicious AP. Experiments show that our attack detection system achieves a higher detection rate.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Alotaibi, B., Elleithy, K.: An empirical fingerprint framework to detect rogue access points. In: Systems, Applications and Technology Conference, pp. 1–7 (2015)
Bahl, P., et al.: Enhancing the security of corporate Wi-Fi networks using DAIR. In: International Conference on Mobile Systems, Applications, and Services, pp. 1–14 (2006)
Beyah, R., Kangude, S., Yu, G., Strickland, B.: Rogue access point detection using temporal traffic characteristics. In: Global Telecommunications Conference, GLOBECOM 2004, vol. 4, pp. 2271–2275. IEEE (2004)
Burns, A., Wu, L., Du, X., Zhu, L.: A novel traceroute-based detection scheme for Wi-Fi evil twin attacks. In: 2017 IEEE Global Communications Conference, GLOBECOM 2017 (2018)
Desmond, L.C.C., Yuan, C.C., Tan, C.P., Lee, R.S.: Identifying unique devices through wireless fingerprinting. In: ACM Conference on Wireless Network Security, WISEC 2008, Alexandria, VA, USA, 31 March–April, pp. 46–55 (2008)
Elleithy, K., Alotaibi, B.: A passive fingerprint technique to detect fake access points. In: IEEE Wireless Telecommunications Symposium (2015)
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)
Hsu, F.H., Wang, C.S., Hsu, Y.L., Cheng, Y.P., Hsneh, Y.H.: A client-side detection mechanism for evil twins. Comput. Electr. Eng. 59, 76–85 (2015)
Jang, R.H., Kang, J., Mohaisen, A., Nyang, D.H.: Rogue access point detector using characteristics of channel overlapping in 802.11n. In: IEEE International Conference on Distributed Computing Systems, pp. 2515–2520 (2017)
Kaushal, P.K.: Survey on evil twin attack. Int. J. Sci. Eng. Res. 4(4), 54–58 (2016)
Kremer, I., Mansour, Y., Perry, M.: Implementing the “wisdom of the crowd”. In: Fourteenth ACM Conference on Electronic Commerce, pp. 605–606 (2013)
Li, M., Liu, Z., Li, J., Jia, C.: Format-preserving encryption for character data. J. Netw. 7(8), 1239 (2012)
Liu, Z., Li, T., Li, P., Jia, C., Li, J.: Verifiable searchable encryption with aggregate keys for data sharing system. Future Gener. Comput. Syst. 78, 778–788 (2018)
Liu, Z., Luo, D., Li, J., Chen, X., Jia, C.: N-Mobishare: new privacy-preserving location-sharing system for mobile online social networks. Int. J. Comput. Math. 93(2), 384–400 (2016)
Mustafa, H., Xu, W.: CETAD: detecting evil twin access point attacks in wireless hotspots. In: Communications and Network Security, pp. 238–246 (2014)
Nivangune, M.K., Vanjale, S., Vanjale, M.: A survey on unauthorized AP detection in WLAN by measuring DNS RTT 4 (2013)
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 (2012). Mobicom 2008
Tang, Z., et al.: Exploiting wireless received signal strength indicators to detect evil-twin attacks in smart homes. Mob. Inf. Syst. 2017(4), 1–14 (2017)
Wei, W., Jaiswal, S., Kurose, J., Towsley, D., Suh, K., Wang, B.: Identifying 802.11 traffic from passive measurements using iterative bayesian inference. IEEE/ACM Trans. Network. 20(2), 325–338 (2012)
Yan, W., Wang, Q., Gao, Z.: Smart home implementation based on internet and WiFi technology. In: Control Conference, pp. 9072–9077 (2015)
Yang, C., Song, Y., Gu, G.: Active user-side evil twin access point detection using statistical techniques. IEEE Trans. Inf. Forensics Secur. 7(5), 1638–1651 (2012)
Yang, Z., Zhou, Z., Liu, Y.: From RSSI to CSI: Indoor localization via channel response. ACM Comput. Surv. 46(2), 1–32 (2014)
Acknowledgments
Our work was supported by the Foundation of the Educational Commission of Tianjin, China (Grant No.2013080), the General Project of Tianjin Municipal Science and Technology Commission under Grant (No.15JCYBJC15600), the Major Project of Tianjin Municipal Science and Technology Commission under Grant (No. 15ZXDSGX00030), and NSFC: The United Foundation of General Technology and Fundamental Research (No. U1536122). The authors would like to give thanks to all the pioneers in this field, and also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, C. et al. (2018). Detecting Evil-Twin Attack with the Crowd Sensing of Landmark in Physical Layer. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11337. Springer, Cham. https://doi.org/10.1007/978-3-030-05063-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-05063-4_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05062-7
Online ISBN: 978-3-030-05063-4
eBook Packages: Computer ScienceComputer Science (R0)