Mathematical Epidemiological Analysis of Dynamics of Delay Attacks on Pull-based Competitive Information Diffusion

Masahiro Sasabe

In Computer Networks, 2020

Abstract

In recent years, competitive information diffusion plays a key role in specific network systems. For example, in the cryptocurrency systems, e.g., Bitcoin, some special nodes, called miners, compete with each other in diffusion races to acquire the system rewards. If the information for diffusion is large, pull-based dissemination is often used to alleviate the communication overhead, where a node notifies a small inventory message to its neighbor(s) before transferring the information itself. On receiving the inventory message, the neighboring node requests the corresponding information from the node. Since the information transfer may require much time due to temporal network/node trouble, the pull-based dissemination generally involves a timeout mechanism. If a timeout occurs, the node retries the information retrieval. A malicious node can conduct a delay attack on the information propagation by exploiting this timeout mechanism, i.e., temporarily interrupting the information transfer after receiving a request. In this paper, a risk of information diffusion with interruption is considered, under which adversaries colluding with a specific source node simultaneously conduct the delay attacks to slow down the information diffusion from competitive source nodes. With the help of the deterministic nonlinear model for the propagation of infectious diseases in mathematical epidemiology, a scalar standby-interrupted-retrieved-attackable (SIRA) model is first developed, which captures the information diffusion with interruption under a well-mixed population. Furthermore, a network SIRA model is proposed by extending the scalar SIRA model to support the information diffusion with interruption over arbitrary networks. Through numerical evaluations, the risk of information diffusion with interruption is quantitatively revealed from the viewpoint of attack scale, attack rate, recovery rate, and network structure.

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Text Reference

Masahiro Sasabe, Mathematical Epidemiological Analysis of Dynamics of Delay Attacks on Pull-based Competitive Information Diffusion, Computer Networks, 180, pp.107383: 1-9, October 2020.

BibTex Reference

@article{sasabe20MathematicalEpidemiologicalAnalysis,
    author = "Sasabe, Masahiro",
    title = "Mathematical {{Epidemiological Analysis}} of {{Dynamics}} of {{Delay Attacks}} on {{Pull-based Competitive Information Diffusion}}",
    year = "2020",
    month = "October",
    journal = "Computer Networks",
    volume = "180",
    pages = "107383: 1-9",
    doi = "10.1016/j.comnet.2020.107383"
}