Visible to the public Misinformation Control in the Internet of Battlefield Things: A Multiclass Mean-Field Game

TitleMisinformation Control in the Internet of Battlefield Things: A Multiclass Mean-Field Game
Publication TypeConference Paper
Year of Publication2018
AuthorsAbuzainab, N., Saad, W.
Conference Name2018 IEEE Global Communications Conference (GLOBECOM)
Date PublishedDec. 2018
ISBN Number978-1-5386-4727-1
KeywordsComputational modeling, considered model, convergence, Curing, false information, finite IoBT case, forward backward sweep method, game theory, Games, human factors, infection cost, Internet of Battlefield Things system, Internet of Things, iobt, IoBT node, massive heterogeneous IoBT system, mean-field equilibrium, Mean-field game, military computing, misinformation attack, misinformation control, misinformation propagation, multiclass agents, optimal probability, optimisation, probability, pubcrawl, QoI, quality of information, resilience, Resiliency, Scalability, Steady-state, telecommunication control

In this paper, the problem of misinformation propagation is studied for an Internet of Battlefield Things (IoBT) system in which an attacker seeks to inject false information in the IoBT nodes in order to compromise the IoBT operations. In the considered model, each IoBT node seeks to counter the misinformation attack by finding the optimal probability of accepting a given information that minimizes its cost at each time instant. The cost is expressed in terms of the quality of information received as well as the infection cost. The problem is formulated as a mean-field game with multiclass agents which is suitable to model a massive heterogeneous IoBT system. For this game, the mean-field equilibrium is characterized, and an algorithm based on the forward backward sweep method is proposed. Then, the finite IoBT case is considered, and the conditions of convergence of the equilibria in the finite case to the mean-field equilibrium are presented. Numerical results show that the proposed scheme can achieve a two-fold increase in the quality of information (QoI) compared to the baseline when the nodes are always transmitting.

Citation Keyabuzainab_misinformation_2018