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.
Nenashev et al. (2026) studied this question.