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We use a directed graph to model the malicious propagation procedure.
Along with the convenience provided by the open online social networks (OSNs) for the users, there are also many burning problems like insecure platform, untrustworthy information, malicious propagation, even illegal cheating.
Fig. 8 Survivability impact of different schemes (a d) in DRS. As shown in Fig. 8, when malicious propagation rate is faster, it will have the lower FAU at start.
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In "Survivable strategy set design for malicious attack propagation in NEMO scenario" [17], Yao et al. propose two novel survivability strategies to handle malicious attack propagation in network mobility (NEMO) scenarios.
Thirdly, we quantitatively show that a search engine accelerates malicious code propagation in SIoTs.
The mathematical model of NEMO survivability for malicious attack propagation has been proposed.
The malicious attack propagation in a mobile network is quite different.
To properly address this issue, this paper proposes two novel survivability strategies to handle malicious attack propagation in NEMO scenario.
Different malicious attack propagation rates will have the same impact on the active users in the beginning.
The rest of this paper is organized as follows: Section 2 describes the system model for malicious attack propagation.
In this paper, we have presented two new survivable strategies when facing malicious attack propagation in NEMO scenario.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com