文章基本信息

标题：A STUDY ON DIFFERENT DATA AGGREGATION TECHNIQUES IN DISTRIBUTED SENSOR NETWORKS
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作者：D. FRANCIS XAVIER CHRISTOPHER ; C. AKALYA
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2017
卷号：6
期号：10
页码：1511-1517
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Mobile devices such as smart phones are gaining an ever-increasing popularity. Most smart phones are equipped with a rich set of embedded sensors such as camera, microphone, GPS, accelerometer, ambient light sensor, gyroscope, and so on. The data generated by these sensors provide opportunities to make sophisticated inferences about not only people (e.g., human activity, health, location, social event) but also their surrounding (e.g., pollution, noise, weather, oxygen level), and thus can help improve people’s health as well as life. To address these problems, this paper proposes an efficient protocol to obtain the Sum aggregate, which employs an additive homomorphic encryption and a novel key management technique to support large plaintext space. The thesis also extends the sum aggregation protocol to obtain the Min aggregate of time-series data. It shows that the proposed protocols are faster than existing solutions, and it has much lower communication overhead. In addition, the paper proposes a new concealed data aggregation scheme which is homomorphic public encryption system based. The proposed scheme has three contributions. First, it is designed for a multi-application environment. The base station extracts application-specific data from aggregated cipher texts. Next, it mitigates the impact of compromising attacks in single application environments. Finally, it degrades the