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Collected data in digital community containing sensitive information about individuals or corporations and such information should be protected. In this paper, a security framework based on (a, k)-anonymity for privacy preserving data collection in digital community is proposed. In our framework, aggregation nodes anonymize the collected data to a basic privacy level. Then, the base stations further anonymize the data to a deeper privacy level with encryption-generalizaiton operations. Experimental results and detailed theory analysis demonstrate that this method is effective in terms of privacy levels and data quality with low resource consumption.
Collected data in digital community containing sensitive information about individuals or corporations and such information should be protected. In this paper, a security framework based on (a, k) -anonymity for privacy preserving data collection in digital community is proposed. then, the base stations further anonymize the data to a deeper privacy level with encryption-generalizaiton operations. Experimental results and detailed theory analysis demonstrate that this method is effective in terms of privacy levels and data quality with low resource consumption.