# Method for Detecting Abnormal Activity in a Group of Mobile Robots
## 2 Related Work
Unfortunately, the process via which this effect was achieved was not fully understood, and the description of the denial of service attack was not given. The following subtypes of robotized systems were defined in Reference [17]: multi-agent robotized systems, mobile sensor networks, MANETs, robotized systems with swarm intelligence, and remotely controlled robots. Each system has its own features from the security point of view, which is why it is important to find a unique approach to and consider features of every system. [PERSON] et al. [18] considered the problem of building protection mechanisms for multi-agent robotic system protection from malicious robots. This paper was devoted to mechanisms of \"soft\" protection or second defense line. The authors constructed the security system with methods which are used in multi-agent computers (MAC). The authors claimed the applicability of [PERSON]'s method [19] and buddy security model (BSM) [20; 21] for MAC protection, which agreed well with decentralized system architecture. In addition to that, they applied social control mechanisms, such as trust and reputation control, for user protection. [PERSON] et al. [22] described their approach based on reputation and trust. They proposed two algorithms to calculate the trust level between nodes. The nodes formed the estimation vector and generated a member's estimation array. These estimations were formed according to the validity of the information and the distance to the target. As a result, the reputation function was described by Weibull-Gnedenko distribution. The drawback of this approach was caused by the fact that trust was calculated at a particular moment of time and for a particular problem. In addition to that, only one parameter was used, namely, the distance to the target. If an intruder carried out a number of various active attacks, which were not connected with data precision and accuracy, this system would not be able to detect that. [PERSON] et al. [23] proposed an approach to algorithm stability estimation based on trust and reputation. The authors used the following parameters for the estimation: interaction radius, number of agents, and percentage of adversaries in the total number of agents. The location of robots was chosen randomly in each experiment. The results reflected the percentage of correctly recognized legitimate agents and malicious agents in the entire network and within the interaction radius. As a result of the experiments, the authors confirmed that the trust model can successfully oppose intruders in any quantity. The main drawbacks of this approach to the network security estimation were the insufficient number of estimation parameters. From the presented parameters, one could only recognize the type of the intruder. The intruder model was described for a certain type of security violation only. An approach to the detection of the malicious node according to the node's behavior was developed in Reference [24]. In this approach, a group of robots followed a set of rules when fulfilling their mission. Then, the robots observed the behavior of others and exchanged relevant information. The behavior of the robots was described by a formal model proposed by the authors. The approach was based on the principle of using a protocol that allowed the robots to detect abnormal behavior of the others under certain conditions and to modify their own behavior to protect other robots from malicious activities. The protocol had two major components. The first one was a monitor of neighbor behavior, comparing it with the agent's own behavior. The second one was the algorithm that allowed combining \"opinions\" of different monitors by communication. The authors carried out the experiments, demonstrating that at least six robots had to monitor the situation to detect intruders properly. The drawback of this method could be summarized as follows: when the system was detecting intruder, it relied only on the behavior of a node, which was characterized by its motions along a trajectory.