Confidentiality Enhancement Using Spread Spectrum Modulation Technique for Aggregated Data in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSN) play a crucial role in transmitting bulk data remotely on Internet of Things (IoT). The data transmitted by the tiny sensor nodes of the network are basically the physical parameters of the environment like temperature, vibration, pressure etc. There exists a huge co-relation in the data sent by the nodes. This bulk data needs to be aggregated in order to conserve the energy of the network and thereby enhance the network lifetime. Although the aggregation might lead to loss of actual data, aggregating helps in reducing energy requirement during transmission which is of primary importance and hence is considered as a suitable method in WSN. Adding confidentiality to aggregated data helps in sending the data more securely. Spread spectrum modulation is a widely used technique to provide confidentiality in communication systems. In this research work, we implement a data aggregation technique and apply the spread spectrum modulation technique to provide confidentiality to the aggregated data that needs to be transmitted from the cluster head node to the gateway. Here, data aggregation process consists of averaging the number of data that are sensed by a sensor node and transmitting only its average value to the gateway. This reduces the amount of data transmission and helps in conserving energy. Further, the spread spectrum technique implements Binary Phase Shift Keying (BPSK) method with Frequency Hopping Spread Spectrum (FHSS) carried out using six different frequencies on MATLAB 2020a. The simulation results evaluate the performance of the system. The graphs are plotted for modulated and demodulated signals, spread and de-spread sequences, Bit Error Rate (BER) of BPSK/ FHSS over Rayleigh flat fading channel, Power Spectral Density (PSD) and Fast Fourier Transform (FFT) of frequency hopped signal. The results show that BER value decreases with increase in Signal to Noise Ratio (SNR). The maximum power consumption in the network is 7.518 mW at 5MHz frequency, for adding confidentiality to the aggregated data to be transmitted. Thus, the proposed work promises efficient energy consumption, longer network lifetimes with added confidentiality.