Data aggregation is an important method to reduce the energy consumption in wireless sensor networks (WSNs), however, performing data aggregation while preserving data confidentiality and integrity is mounting a challenge. The existing solutions either have large communication and computation overheads or produce inaccurate results. This paper proposes a novel secure data aggregation scheme based on homomorphic encryption in WSNs. The scheme adopts a symmetric-key homomorphic encryption to protect data privacy and combines it with homomorphic signature to check the aggregation data integrity. In addition, during the decryption of aggregated data, the base station is able to classify the encrypted and aggregated data based on the encryption keys. Simulation results and performance analysis show that our mechanism requires less communication and computation overheads than previously known methods. It can effectively preserve data privacy, check data integrity, and achieve high data transmission efficiency. Also, it performs accurate data aggregation rate while consuming less energy to prolong network lifetime.

Abstract-

Medical wireless sensor networks (MWSNs) provide efficient solutions to the ubiquitous healthcare systems. Deployment of MWSNs for healthcare monitoring minimizes the need for healthcare professionals and helps the patients and elderly people to safely maintain an independent life. In hospitals, medical data sensors on patients produce an enormous volume of increasingly diverse real-time data. However, it is still critical to efficiently aggregate the different types of MWSNs data to the central servers. The security of collected and transmitted data from medical sensors is critical, whether inside the network or when stored at central servers. Efficient and secure aggregation of data is thus very essential to ensure integrity of data delivery, as well as the privacy of these data. In this research, we propose a priority-based compressed data aggregation scheme with integrity preservation to improve the aggregation efficiency of different types of health data. We use compressed sensing as a sampling procedure to reduce the communication overhead and minimize power consumption. Then, the compressed data are encrypted, and integrity is protected by a cryptographic hash algorithm to preserve data integrity. Finally, according to different data priorities, we apply an aggregation function and then send the data for diagnosis. The security analysis focuses on security properties assured by our scheme. Then, we will present experimental results for the evaluation of the proposed system on e-health sensor platform.

Abstract. In this paper, we present an adaptive architecture for the transport of VoIP traffic over heterogeneous wired/wireless Internet environments. This architecture uses a VoIP gateway associated with an 802.11e QoS enhanced access point (QAP) to transcode voice flows before their transmissions over the wireless channel. The instantaneous bit rate is determined by a control mechanism based on the estimation of channel congestion state. Our mechanism dynamically adapts audio codec bit rate using a congestion avoidance technique so as to preserve acceptable levels of quality. A case study presenting the results relative to an adaptive system transmitting at bit rates typical of G.711 PCM (64 kbit/s) and G.726 ADPCM (40, 32, 24 and 16 kbit/s) speech coding standards illustrates the performance of the proposed framework. We perform extensive simulations to compare the performance between our adaptive audio rate control and TFRC mechanism. The results show that the proposed mechanism achieves better voice transmission performance, especially when the number of stations is fairly large.

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