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Complex networks tend to display communities which are groups of nodes cohesively connected among themselves in one group and sparsely connected to the remainder of the network. Detecting such communities is an important computational problem, since it provides an insight into the functionality of networks. Further, investigating community structure in a dynamic network, where the network is subject to change, is even more challenging. This paper presents a game-theoretical technique for detecting community structures in dynamic as well as static complex networks. In our method, each node takes the role of a player that attempts to gain a higher payoff by joining one or more communities or switching between them. The goal of the game is to reveal community structure formed by these players by finding a Nash-equilibrium point among them. To the best of our knowledge, this is the first game-theoretic algorithm which is able to extract overlapping communities from either static or dynamic networks. We present the experimental results illustrating the effectiveness of the proposed method on both synthetic and real-world networks.
We present the design and analysis of a multi-level game-theoretic model of hierarchical policy-making, inspired by policy responses to the COVID-19 pandemic. Our model captures the potentially mismatched priorities among a hierarchy of policy-makers
Advanced Persistent Threats (APTs) infiltrate cyber systems and compromise specifically targeted data and/or resources through a sequence of stealthy attacks consisting of multiple stages. Dynamic information flow tracking has been proposed to detect
Advanced Persistent Threats (APTs) are stealthy customized attacks by intelligent adversaries. This paper deals with the detection of APTs that infiltrate cyber systems and compromise specifically targeted data and/or infrastructures. Dynamic informa
Federated learning is a distributed learning paradigm where multiple agents, each only with access to local data, jointly learn a global model. There has recently been an explosion of research aiming not only to improve the accuracy rates of federate
Coded distributed computing (CDC) has emerged as a promising approach because it enables computation tasks to be carried out in a distributed manner while mitigating straggler effects, which often account for the long overall completion times. Specif