A method of protection against the Sybil attack based on the analysis of the correlogram of the electromagnetic field power map of network traffic
Abstract
A method of protection against the Sybil attack based on the analysis of the correlogram of the electromagnetic field power map of network traffic
Incoming article date: 02.12.2025This paper discusses a method for countering Sybil attacks in distributed systems based on the analysis of electromagnetic power maps of the temporal characteristics of network traffic. The key hypothesis is that multiple Sybil identifiers controlled by a single attacker node exhibit statistically significant correlation in their network activity patterns, which can be identified using a correlogram. A method for detecting Sybil attacks in wireless networks is proposed based on the analysis of correlograms of electromagnetic signal power maps. The method exploits the statistical properties of power profiles arising from the correlation of network activity of Sybil nodes controlled by a single attacker. A protection system architecture has been developed, including modules for network activity monitoring, correlogram calculation, clustering, and anomaly detection. A set of 10 correlogram parameters is introduced for attack identification, including profile variance, randomness and periodicity coefficients, spectral density, and correlation characteristics. Experimental testing on a millimeter-wave radar station demonstrated detection accuracy ranging from 83.2% to 97.4%. To improve the method's effectiveness, the use of deep neural networks after accumulating a sufficient amount of data is proposed. The proposed method enables the identification and denial of compromised identifiers, increasing the resilience of P2P networks, blockchain systems, and distributed ledgers.
Keywords: Sybil attack, distributed systems security, correlogram, network traffic analysis, time series, autocorrelation, anomaly detection