Measure of invulnerability for command and control network based on mission link

Effectiveness Evaluation Method of Application of Mobile Communication System Based on Factor Analysis

The application mode of army mobile communication networks is closely related to combat mission and application environment. Different combat missions and application environments result in different network structures and different service priorities, which requires a semi-automatic system to support the network scheme design. Therefore, evaluating the efficiency of network schemes generated by automatic planning is a problem that needs to be urgently addressed. In the past, researchers have proposed a variety of methods to evaluate the effectiveness of mobile communication systems, most of which are based on simulation methods and ignore the historical data of network usage. This paper studies an effectiveness evaluation method of mobile communication network design schemes and proposes a design scheme for the evaluation and optimization of network plans. Furthermore, the improved method of effectiveness evaluation based on factor analysis is discussed in detail. The method not only effectively uses historical data but also reduces the amount of data collection and calculation. In order to adapt to the preference requirements of different task scenarios, a decision preference setting method based on cluster analysis is proposed, which can render the output optimization result more reasonable and feasible.

Robustness of Internet of Battlefield Things (IoBT): A Directed Network Perspective

Through the combination of various intelligent devices and the Internet to form a large-scale network, the Internet of Things (IoT) realizes real-time information exchange and communication between devices. IoT technology is expected to play an essential role in improving the combat effectiveness and situation awareness ability of armies. The interconnection between combat equipment and other battlefield resources is referred to as the Internet of Battlefield Things (IoBT). Battlefield real-time data sharing and the cooperative decision-making among commanders are highly dependent on the connectivity between different combat units in the network. However, due to the wireless characteristics of communication, a large number of communication links are directly exposed in the complex battlefield environment, and various cyber or physical attacks threaten network connectivity. Therefore, the ability to maintain network connectivity under adversary attacks is a critical property for the IoBT. In this work, we propose a directed network model and connectivity measurement of the IoBT network. Then, we develop an optimal attack strategy optimization model to simulate the optimal attack behavior of the enemy. By comparing with the disintegration effect of some benchmark strategies, we verify the optimality of the model solution and find that the robustness of the IoBT network decreases rapidly with an increase of the unidirectional communication links in the network. The results show that the adversary will change the attack mode according to the parameter settings of attack resources and network communication link density. In order to enhance the network robustness, we need to adjust the defense strategy in time to deal with this change. Finally, we validated the model and theoretical analysis proposed in this paper through experiments on a real military network.

DR-SCIR Public Opinion Propagation Model with Direct Immunity and Social Reinforcement Effect

The DR-SCIR network public opinion propagation model was employed to study the characters of S-state users stopping transmitting information for the first time and secondary transmission of immune users. The model takes into account symmetry and complexity such as direct immunization and social reinforcement effect, proposes the probability of direct immunity Psr and the probability of transform from the immune state to the hesitant state Prc, and divides public opinion information into positive public opinion and negative public opinion based on whether the public opinion information is confirmed. Simulation results show that, when direct immunity Psr = 0.5, the density of I-state nodes in the model decreased by 54.12% at the peak index; when the positive social reinforcement effect factor b = 10, the density of I-state nodes in the model increased by 16.67% at the peak index; and when the negative social reinforcement effect factor b = -10, the density of I-state nodes in the model decreased by 55.36% at the peak index. It shows that increasing the positive social reinforcement effect factor b can promote the spread of positive public opinion, reducing the negative social reinforcement effect factor b can control the spread of negative public opinion, and direct immunization can effectively suppress the spread of public opinion. This model can help us better analyze the rules of public opinion on social networks, so as to maintain a healthy and harmonious network and social environment.