An analysis of the physical characteristics of the node, which can be attacked by an attacker. A method of detecting a damaged node with a violation of the physical characteristics of the network node, which is based on the use of probability functions, calculation of the confidence interval and the probability of deviation of current values from the confidence interval. Its novelty lies in the possibility of detecting a damaged node by estimating the current value of the function in the confidence interval, without comparing the distribution function of the current node with the reference distribution. The analysis of physical parameters of network nodes for detection of the malefactor in contrast to existing systems of detection of attacks which allow to carry out only the analysis of network traffic is carried out. Based on the developed algorithm by modeling the transmission of chaotic signals in a wireless sensor network, the effectiveness of attack detection is determined through the analysis of residual energy and node congestion parameters, expanding the range of attacks that the network is able to counteract compared to system analogues.
During the simulation of the behavior of the wireless sensor network, it was determined that the data transmission processes are chaotic. Therefore, to enhance the security of data transmission in a chaotic mode, we have proposed an encryption algorithm using dynamic chaos, coordinate delay methods and singular spectral analysis. A comparative analysis of the parameters of the input and output sequences of the developed encryption algorithm based on dynamic chaos with standard data encryption algorithms is performed. It is established that the encryption parameters that are characteristic of the original sequences of the encryption algorithm using dynamic chaos are not worse than the encryption parameters obtained for the source sequences of standard encryption algorithms. Estimation of node load by means of threshold analysis of their current values in the confidence interval is used to detect network deviations during a cyberattack. The developed algorithm allows to diagnose attacks such as "Denial of Service" and "Sibyl" at the beginning of their appearance and to determine possible ways to avoid them.
