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Dynamic Task Scheduler for Real Time Requirement in Cloud Computing System Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Detecting Evil-Twin Attack with the Crowd Sensing of Landmark in Physical Layer

Authors : Chundong Wang, Likun Zhu, Liangyi Gong, Zheli Liu, Xiuliang Mo, Wenjun Yang, Min Li, Zhaoyang Li

Published in: Algorithms and Architectures for Parallel Processing

Publisher: Springer International Publishing

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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.

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previous chapter Fine-Grained Attribute-Based Encryption Scheme Supporting Equality Test
next chapter Security Extension and Robust Upgrade of Smart-Watch Wi-Fi Controller Firmware
Literature
1.
Alotaibi, B., Elleithy, K.: An empirical fingerprint framework to detect rogue access points. In: Systems, Applications and Technology Conference, pp. 1–7 (2015)
2.
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)
3.
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)
4.
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)
5.
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)
6.
Elleithy, K., Alotaibi, B.: A passive fingerprint technique to detect fake access points. In: IEEE Wireless Telecommunications Symposium (2015)
7.
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)CrossRef
8.
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)CrossRef
9.
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)
10.
Kaushal, P.K.: Survey on evil twin attack. Int. J. Sci. Eng. Res. 4(4), 54–58 (2016)
11.
Kremer, I., Mansour, Y., Perry, M.: Implementing the “wisdom of the crowd”. In: Fourteenth ACM Conference on Electronic Commerce, pp. 605–606 (2013)
12.
Li, M., Liu, Z., Li, J., Jia, C.: Format-preserving encryption for character data. J. Netw. 7(8), 1239 (2012)
13.
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)CrossRef
14.
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)MathSciNetCrossRef
15.
Mustafa, H., Xu, W.: CETAD: detecting evil twin access point attacks in wireless hotspots. In: Communications and Network Security, pp. 238–246 (2014)
16.
Nivangune, M.K., Vanjale, S., Vanjale, M.: A survey on unauthorized AP detection in WLAN by measuring DNS RTT 4 (2013)
17.
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 2008CrossRef
18.
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)
19.
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)CrossRef
20.
Yan, W., Wang, Q., Gao, Z.: Smart home implementation based on internet and WiFi technology. In: Control Conference, pp. 9072–9077 (2015)
21.
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)CrossRef
22.
Yang, Z., Zhou, Z., Liu, Y.: From RSSI to CSI: Indoor localization via channel response. ACM Comput. Surv. 46(2), 1–32 (2014)CrossRef
Metadata
Title
Detecting Evil-Twin Attack with the Crowd Sensing of Landmark in Physical Layer
Authors
Chundong Wang
Likun Zhu
Liangyi Gong
Zheli Liu
Xiuliang Mo
Wenjun Yang
Min Li
Zhaoyang Li
Copyright Year
2018
Book
Algorithms and Architectures for Parallel Processing

Print ISBN: 978-3-030-05062-7

Electronic ISBN: 978-3-030-05063-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-05063-4_19

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