The demand for ef?cient knowledge dissemination/access techniquesto ?nd the relevant data from among a sensor network has led to the development of knowledge-centric sensor networks (DCS), where the sensor data ascontrast to sensor nodes are named based mostly on attributes like event typeor geographic location. However, saving knowledge within a network also createssecurity issues due to the shortage of tamper-resistance of the sensor nodesand the unattended nature of the sensor network. For example, an attackermay merely locate and compromise the node storing the event of his interest.To address these security issues, we gift pDCS, a privacy-enhancedDCS network which offers totally different levels of data privacy based mostly on completely different cryptographic keys. In addition, we have a tendency to propose many query optimizationtechniques primarily based on Euclidean Steiner Tree and Keyed Bloom Filter tominimize the query overhead whereas providing sure question privacy. Finally,detailed analysis and simulations show that the Keyed Bloom Filter schemecan signi?cantly cut back the message overhead with the same level of querydelay and maintain a terribly high level of query privacy
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