Intrusion Detection in the Structure of Signal-Code Design in Cyber-Physical Systems of Swarm Small Aerial Vehicles Group Interaction

The fault tolerance of a swarm of small aerial vehicles (SAVs) is directly dependent on the reliability of data transmitted over communication channels. One of the key threats is the intentional distortion of signal sequences by an attacker, such as Barker codes or M-sequences, which are used for synchronization and control of the swarm. Such an attack can disable the entire swarm. The aim of this study is to develop a method for detecting such intrusions. The proposed algorithm analyzes mathematical expressions that describe the sidelobes’ levels of the autocorrelation function of the code. This approach not only detects unauthorized changes but also accurately identifies the location and magnitude of the distorted element. The conducted experiments confirm the high accuracy of the algorithm. The practical significance of the work lies in the possibility of integrating this method into the security subsystem of group interaction for small aerial vehicles. This creates a mechanism for active anomaly detection in communication channels: when a threat is detected, the swarm can respond promptly by switching to a backup channel, requesting data retransmission, or isolating the compromised channel, which in turn enhances the survivability and fault tolerance of the system’s functioning within the group.

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Publication Details

Journal
Future Internet
Published
2026-04-01
DOI
https://doi.org/10.3390/fi18040183
Primary Topic
Cybersecurity and Information Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Intrusion Detection in the Structure of Signal-Code Design in Cyber-Physical Systems of Swarm Small Aerial Vehicles Group Interaction

Renata I. Chembarisova, Oleg V. Varlamov, Vadim A. Nenashev, Svetlana S. Dymkova
Future Internet
Cybersecurity and Information Systems
article

Intrusion Detection in the Structure of Signal-Code Design in Cyber-Physical Systems of Swarm Small Aerial Vehicles Group Interaction

Renata I. Chembarisova, Oleg V. Varlamov, Vadim A. Nenashev, Svetlana S. Dymkova
article en

Abstract

The fault tolerance of a swarm of small aerial vehicles (SAVs) is directly dependent on the reliability of data transmitted over communication channels. One of the key threats is the intentional distortion of signal sequences by an attacker, such as Barker codes or M-sequences, which are used for synchronization and control of the swarm. Such an attack can disable the entire swarm. The aim of this study is to develop a method for detecting such intrusions. The proposed algorithm analyzes mathematical expressions that describe the sidelobes’ levels of the autocorrelation function of the code. This approach not only detects unauthorized changes but also accurately identifies the location and magnitude of the distorted element. The conducted experiments confirm the high accuracy of the algorithm. The practical significance of the work lies in the possibility of integrating this method into the security subsystem of group interaction for small aerial vehicles. This creates a mechanism for active anomaly detection in communication channels: when a threat is detected, the swarm can respond promptly by switching to a backup channel, requesting data retransmission, or isolating the compromised channel, which in turn enhances the survivability and fault tolerance of the system’s functioning within the group.

Future InternetVol. 18(4)
Saint Petersburg State University of Aerospace and Instrumentation (RU), Saint-Petersburg State University of Technology and Design (RU), Moscow Technical University of Communication and Informatics (RU), Institute of Radio and Information Systems (IRIS)
Russian Science Foundation
Openalex Percentile: Top 32%
Cybersecurity and Information Systems
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Intrusion Detection in the Structure of Signal-Code Design in Cyber-Physical Systems of Swarm Small Aerial Vehicles Group Interaction — Renata I. Chembarisova, Oleg V. Varlamov, et al. · Future Internet (2026) | TGRS Research Map | TGRS