194 research outputs found
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
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