On the Role of Risk Perceptions in Cyber Insurance Contracts

Risk perceptions are essential in cyber insurance contracts. With the recent surge of information, human risk perceptions are exposed to the influences from both beneficial knowledge and fake news. In this paper, we study the role of the risk perceptions of the insurer and the user in cyber insurance contracts. We formulate the cyber insurance problem into a principal-agent problem where the insurer designs the contract containing a premium payment and a coverage plan. The risk perceptions of the insurer and the user are captured by coherent risk measures. Our framework extends the cyber insurance problem containing a risk-neutral insurer and a possibly risk-averse user, which is often considered in the literature. The explicit characterizations of both the insurer's and the user's risk perceptions allow us to show that cyber insurance has the potential to incentivize the user to invest more on system protection. This possibility to increase cyber security relies on the facts that the insurer is more risk-averse than the user (in a minimization setting) and that the insurer's risk perception is more sensitive to the changes in the user's actions than the user himself. We investigate the properties of feasible contracts in a case study on the insurance of a computer system against ransomware.Comment: 6 pages, 3 figure

Communication-Efficient Distributed Machine Learning over Strategic Networks: A Two-Layer Game Approach

This paper considers a game-theoretic framework for distributed learning problems over networks where communications between nodes are costly. In the proposed game, players decide both the learning parameters and the network structure for communications. The Nash equilibrium characterizes the tradeoff between the local performance and the global agreement of the learned classifiers. We introduce a two-layer algorithm to find the equilibrium. The algorithm features a joint learning process that integrates the iterative learning at each node and the network formation. We show that our game is equivalent to a generalized potential game in the setting of symmetric networks. We study the convergence of the proposed algorithm, analyze the network structures determined by our game, and show the improvement of the social welfare in comparison with the distributed learning over non-strategic networks. In the case study, we deal with streaming data and use telemonitoring of Parkinson's disease to corroborate the results.Comment: 20 pages, 9 figure

Active Multiple Plasmon-Induced Transparency with Graphene Sheets Resonators in Mid-Infrared Frequencies

A multiple plasmon-induced transparency (PIT) device operated in the mid-infrared region has been proposed. The designed model is comprised of one graphene ribbon as main waveguide and two narrow graphene sheets resonators. The phase coupling between two graphene resonators has been investigated. The multimode PIT resonances have been found in both cases and can be dynamically tuned via varying the chemical potential of graphene resonators without optimizing its geometric parameters. In addition, this structure can get multiple PIT effect by equipping extra two sheets on the symmetric positions of graphene waveguide. The simulation results based on finite element method (FEM) are in good agreement with the resonance theory. This work may pave new way for graphene-based thermal plasmonic devices applications