A Secure Big Data Streams Analytics Farmework for Disater Management on Cloud

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
2016, pp. 1218 - 1225 (8)
Issue Date:
2016-12-14
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Cloud computing and big data analysis are gaining lots of interest across a range of applications including disaster management. These two technologies together provide the capability of real-time data analysis not only to detect emergencies in disaster areas, but also to rescue the affected people. This paper presents a framework that supports emergency event detection and alert generation by analyzing the data stream, which includes efficient data collection, data aggregation and alert dissemination. One of the goals for such a framework is to support an end-to-end security architecture to protect the data stream from unauthorized manipulation as well as leakage of sensitive information. The proposed system provides support for both data security punctuation and query security punctuation. This paper presents the proposed architecture with a specific focus on data stream security. It also briefly describes the implementation of security aspects of the architecture.
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