These methods, however, have two limitations. First, the communication cost for network construction is considerably high. Second, they do not support data integrity. There are two methods for supporting data integrity, iCPDA and iPDA. But they have high communication cost due to additional integrity checking messages. To resolve this problem, we propose a novel Hilbert-curve based data aggregation scheme that enforces data privacy and data integrity for WSNs. To minimize communication cost, we utilize a tree-based network structure for constructing networks and aggregating data. To preserve data privacy, we make use of both a seed exchange algorithm and Hilbert-curve based data encryption. To support data integrity, we use an integrity checking algorithm based on the PIR technique by directly communicating between parent and child nodes. Finally, through a performance analysis, we show that our scheme outperforms the existing methods in terms of both energy efficiency and privacy preservation.
Data aggregation techniques have been widely used in wireless sensor networks (WSNs) to solve the energy constraint problems of sensor nodes. They can conserve the significant amount of energy by reducing data packet transmission costs. However, many data aggregation applications require privacy and integrity protection of the real data while transmitting data from the sensing nodes to a sink node. The existing schemes for supporting both privacy and integrity, that is, iCDPA, and iPDA, suffer from high communication cost, high computation cost, and data propagation delay. To resolve the problems, we propose a signature-based data security technique for protecting sensitive data aggregation in WSNs. To support privacy-preserving data aggregation and integrity checking, our technique makes use of the additive property of complex numbers. Out of two parts of a complex number, the real part is used to hide the sampled data of a sensor node from its neighboring nodes and adversaries, whereas the imaginary part is used for data integrity checking at both data aggregators and the sink node. Through a performance analysis, we prove that our privacy-preserving data aggregation scheme outperforms the existing schemes up to 50% in terms of communication and computation overheads as well as up to 3 times in terms of integrity checking and data propagation delay.
In this paper, we design an intelligent system architecture for dealing with context-aware application services in pervasive computing environment. The context-aware intelligent system architecture is composed of middleware, context server, and client. The middleware component of our intelligent system architecture plays an important role in recognizing a moving node with mobility by using a Bluetooth wireless communication technology as well as in executing an appropriate execution module according to the context acquired from a context server. The context server functions as a manager that efficiently stores into the database server context information, such as user's current status, physical environment, and resources of a computing system. To verify the usefulness of our context-aware intelligent system architecture, we finally develop a contextaware application to provide users with a music playing service in pervasive computing environment.
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