Abstract
Mobile cloud computing breaks the limitation of mobile terminal hardware, and makes mobile terminal easier to achieve portable data accessing and intelligent load balancing. However, its three levels of “user-environment-service” are more prone to appear security problems. From the perspective of user credibility, we propose an analysis strategy of user abnormal behavior in mobile cloud environment. In our framework, user behaviors are normalized to the fragment identifiers of “user-timing sequence-operation” with the same length, offset and amplitude. The experimental results have shown that the classifying accuracy increased comparing to traditional methods. Besides, as seen from experimental results, the scheme could also improve the recognition speed.
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Acknowledgements
This work was partially supported by the National Natural Science Foundation of China (61602155, U1404611, 61370221, U1204614), in part by Program for Science & Technology Innovative Research Team in University of Henan Province (14IRTSTHN021), and in part by the Program for Science & Technology Innovation Talents in the University of Henan Province (14HASTIT045, 16HASTIT035), in part by Henan science and technology innovation outstanding talent (174100510010) and Training plan of Henan youth backbone teachers (2014GGJS-053, 2015GGJS-047).
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Zheng, R., Chen, J., Liu, K. et al. A User Recognition Strategy Under Mobile Cloud Environment. Wireless Pers Commun 102, 3749–3758 (2018). https://doi.org/10.1007/s11277-018-5406-1
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DOI: https://doi.org/10.1007/s11277-018-5406-1