Description: The experience of carrying out the Operation of the Joint Forces shows that one of the decisive factors for the successful implementation of combat missions is the timely provision of troops (forces) to current intelligence information. One way to ensure intelligence gathering in real time is to use wireless sensor networks deployed directly on the collision line. Wireless Sensor Network (Wireless Sensor Network) is a distributed network of small nodes (sensors) with functions for gathering, processing and transmitting data about the state of the environment. Data transfer is carried out using IEEE 802.11n technology (broadband harmonic signals with different modulation types are used as carriers). However, the presence of advanced electronic warfare means by the opponent calls into question the wireless security interference: these types of signals do not fully meet the requirements of secrecy. Because they differ from the noise of observation with correlation, spectral and nonlinear analysis. That is why there is a significant danger that the enemy will disclose the fact that a wireless sensory intelligence information network is operating, which in turn can lead to hostile acts on the radio channel of the data transmission. The basis of destructive actions on the management system should be understood to be the use of radio-electronic intelligence and radio-electronic suppressing devices. Analysis of literature shows that one of the promising approaches to increasing the secrecy of data transmission channels in wireless sensor networks is the use of chaotic processes that, according to their statistical and dynamic characteristics, are similar to the noise of observation. Thus, the purpose of the work is to justify the possibility of using chaotic processes to organize the radio channel of data transmission in wireless sensory networks while performing tasks for the collection of intelligence information.
Keywords: wireless sensor network, illegal armed formations, chaotic process, secrecy, data transfer, non-linear analysis of observations, correlation analysis
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