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Journal of Applied Mathematics
Volume 2014, Article ID 594501, 10 pages
http://dx.doi.org/10.1155/2014/594501
Research Article

Linear SVM-Based Android Malware Detection for Reliable IoT Services

1Department of Computer Science, Kangwon National University, 1 Kangwondaehak-gil, Gangwon-do 200-701, Republic of Korea
2Department of Computer and Information Science, Korea University, 2511 Sejong-ro, Sejong-si 339-770, Republic of Korea

Received 31 January 2014; Accepted 22 July 2014; Published 3 September 2014

Academic Editor: Young-Sik Jeong

Copyright © 2014 Hyo-Sik Ham et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Abdulaziz Y. Barnawi, and Ismail M. Keshta, “Energy Management in Wireless Sensor Networks Based on Naive Bayes, MLP, and SVM Classifications: A Comparative Study,” Journal of Sensors, vol. 2016, pp. 1–12, 2016. View at Publisher · View at Google Scholar
  • Parwinder Kaur Dhillon, and Sheetal Kalra, “A lightweight biometrics based remote user authentication scheme for IoT services,” Journal of Information Security and Applications, 2017. View at Publisher · View at Google Scholar