Wireless sensor networks are specialized networks, geographically dispersed monitors that keep track of environmental external factors and conduct the collected information to a centralized opinion. The rapid growth of wireless sensor networks and its connected have pushed the saturation level of the communication. Moreover, the information passed is prone to the attacks and hence researchers have considered these as crucial factors in wireless sensor networks. Physical layer security is the one of the main approaches to ensure the secrecy of wireless sensor networks and has been attained with several encryption and signal processing approach. In our approach we propose a novel Projection Pursuit Gaussian Process regression (PPGPR) technique to analyze the diverse secrecy of physical layer in wireless sensor networks. The proposed approach is utilized to safeguard the sensitive data with secured physical layer. Simulations are performed and made an analogous study with state-of-art works to ensure the secrecy of the proposed work. The proposed work can use for the secured wireless communication with higher secrecy capacity than the existing approaches. The performance is analyzed with the parameters such as secrecy capacity, secrecy outage probability, packet delivery ratio, secrecy throughput, and energy consumption.
Wireless sensor networks are specialized networks, geographically dispersed monitors that keep track of environmental external factors and conduct the collected information to a centralized opinion. The rapid growth of wireless sensor networks and its connected have pushed the saturation level of the communication. Moreover, the information passed is prone to the attacks and hence researchers have considered these as crucial factors in wireless sensor networks. Physical layer security is the one of the main approaches to ensure the secrecy of wireless sensor networks and has been attained with several encryption and signal processing approach. In our approach we propose a novel Projection Pursuit Gaussian Process regression (PPGPR) technique to analyze the diverse secrecy of physical layer in wireless sensor networks. The proposed approach is utilized to safeguard the sensitive data with secured physical layer. Simulations are performed and made an analogous study with state-of-art works to ensure the secrecy of the proposed work. The proposed work can use for the secured wireless communication with higher secrecy capacity than the existing approaches. The performance is analyzed with the parameters such as secrecy capacity, secrecy outage probability, packet delivery ratio, secrecy throughput, and energy consumption.
Secrecy Diversity Analysis is to improve Physical Layer Security (PLS) in Wireless Sensor Networks (WSNs). Wireless Sensor Networks (WSNs) are more susceptible to security risks owing to the broadcast characteristics of wireless communication, necessitating the protection of sensitive data. The research examines the application of diversity strategies to enhance secrecy performance in wireless communication networks. Utilizing variety, including antenna diversity and channel diversity, the system can bolster resilience against eavesdroppers and augment the overall secrecy capacity. Employing MATLAB alongside Simulink as the simulation instrument, multiple secrecy performance measures are assessed, including secrecy capacity and secrecy outage probability. The simulation results indicate that the incorporation of diversity approaches at the physical layer markedly enhances the security of wireless sensor networks, diminishing the probability of eavesdropping and augmenting system resiliency. This research emphasizes the significance of integrating PLS with diversity approaches to improve security in resource-limited wireless systems such as WSNs.
The applications of Wireless Sensor Networks (WSNs) are widespread in areas such as environmental monitoring, industrial automation, healthcare and smart infrastructures, where secure and reliable wireless communication is essential. The nature of a wireless channel, however, lends itself to the problem of eavesdropper-directed wireless sensor networking, interception and unauthorized access. This paper presents a secure physical layer communication system featuring the combination of channel estimator, physical layer key generator, artificial noise generator and adaptive power allocator to increase the confidentiality of physical layer communications and simultaneously achieve energy efficiency. A hybrid security mechanism is used, which takes advantage of the channel characteristics to create secret keys and to make the eavesdropper's signal reception worse by introducing controlled artificial noise. Key performance parameters considered for simulation-based evaluation are secrecy capacity, BER, PDR, Throughput, Energy consumption and Network lifetime. Results show that the secrecy capacity is 6.3 bps/Hz, the packet delivery ratio is 98.7%, the bit error rate is 10⁻⁶, and the network lifetime is 1675 rounds. The proposed framework is much more effective in terms of both communication security and energy efficiency than the traditional WSNs security schemes.
The wireless sensor network (WSN) plays a fundamentally important role in the realization of Internet of Things and Industry 4.0. In this article, we study the physical layer security performance of a large-scale ad hoc and homogeneous WSN. To accurately evaluate the secrecy performance of the large-scale WSN, we take into account the randomness of the interfering nodes (both in terms of the number of nodes and their respective position) based on Poisson point process in our analysis. We derive novel expressions for the average secrecy capacity and secrecy outage probability, including the effects of fading, path loss, and the network's spatial randomness. The results demonstrate the impacts of several factors such as node intensity and transmission power in large-scale WSN on secrecy performance, which should be seriously taken into consideration while designing WSNs.
In smart cities, the ubiquitous network connections and high data rate services are provided to afford effective service of real-time monitoring and responses. With the development of the 5G mobile communication technology, the wireless sensor mobile communication networks in the smart city have become a hot issue for academic researches. Due to the openness of wireless channels, the physical layer security of the wireless mobile sensor mobile communication networks in smart city encounters severe challenges. In this paper, based on Wyner's wiretap model, the secrecy performance of the wireless mobile sensor communication networks over 2-Nakagami fading channels is investigated. We derive the exact secure outage probability (SOP) and the probability of strictly positive secrecy capacity expressions for two transmit antenna selection (TAS) schemes. The exact closed-form expressions for the lower bound on the SOP are also derived using the optimal TAS scheme. Then, the system secrecy performance is verified and analyzed by Monte Carlo simulations under different conditions. The simulation results show that the analytical results match perfectly with the Monte Carlo simulation results. Increasing the number of transmit antennas can improve secrecy performance.
Growing need for secure wireless communication in networks like Internet of Things (IoT), 5G, and future 6G has raised concerns about efficient ways to ensure security. Cryptography techniques are considered to be efficient from the standpoint of providing security; however, they are also limited in computational complexity, energy consumption, and key management. In order to overcome the above-mentioned issue, it is possible to employ Physical Layer Security (PLS). Using unique characteristics of wireless communication channel, it is possible to enhance the confidentiality of the process. The current research paper analyzes the PLS approach for investigation of partial secrecy in case wireless channel operates under such fading distributions as Rayleigh, Rician, and Nakagami-m. The diversity-based approach for enhancing physical layer security is employed through use of such diversity types as Selection Combining (SC), Maximal Ratio Combining (MRC), and Cooperative Diversity. Analysis of performance of such a system is performed with the help of MATLAB simulations using the following parameters: Secrecy Capacity, Generalized Secrecy Outage Probability (GSOP), Average Information Leakage Rate (AILR), Average Fractional Equivocation (AFE), and Secrecy Throughput. The results of simulations demonstrate the advantage of diversity approach with respect to ensuring secure wireless communications at different SNR values. Among all kinds of diversity, MRC performs better than others due to its efficient signal combining capability.
Information security has been a very important issue in wireless networks. With the ever-increasing amount of data being exchanged over wireless networks, the confidentiality of information needs to be protected from unauthorized users called eavesdropper. Due to the broadcast nature of the wireless medium, the transmissions between legitimate users maybe overheard and intercepted by the unauthorized parties, which makes wireless transmission vulnerable to potential eavesdropping attacks. The security of wireless communications plays an increasingly important role in the cybercrime defense against unauthorized activities. We consider the wireless physical layer security which has been explored for the sake of enhancing the protection of wireless communications against eavesdroppers. We consider the problem of secret communication through Rayleigh fading channel in the presence of an eavesdropper in which the transmitter knows the channel state information of both the main and eavesdropper channel. Then, we analyze the average capacity of the main channel and eavesdropper channel from which an expression of secrecy capacity is derived based on the cumulative distribution function and probability density function of the signal to noise ratio. We also analyze an expression for the symbol error rate of the main channel, and the outage probability is obtained for the main transmission. Finally, we perform the numerical results in MATLAB.