Abstract
Malware posts an increasing threat to the security of cyberspace, given the growing popularity of wireless networks. In this paper, we propose a hypergraph-based model to describe the malware propagation over a large-scale wireless network, where the hypergraph adequately describes the limited range and Internet-independent transmission over the wireless network. In the proposed model, the malware on an infected device will attack the wireless router and infect all normal devices on the wireless network. From a heterogeneous mean-field approach, we obtain the malware outbreak threshold. Through theoretical analysis and numerical simulations, we show that the malware pandemic on large-scale wireless networks depends mainly on the number of devices covered by the wireless network and the nature of the malware. Moreover, we find that isolating connections on the Internet does not completely inhibit the malware pandemic. These phenomena are also reflected in the hypergraph constructed from real data. We demonstrate that heterogeneous distributions of devices on wireless networks can lead to malware outbreaks more easily. Finally, we show that malware propagation on large-scale wireless networks is more sensitive to the number of initially infected devices compared to the propagation on the Internet. © 2023 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 3767-3778 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Network Science and Engineering |
| Volume | 10 |
| Issue number | 6 |
| Online published | 17 May 2023 |
| DOIs | |
| Publication status | Published - Nov 2023 |
Funding
The work of Chengyi Xia was supported by the Tianjin Municipal Natural Science Foundation under Grant 22JCZDJC00550. This work was supported in part by the National Natural Science Foundation of China under Grant 62173247, and in part by Hong Kong Research Grants Council through General Research Funds under Grant CityU 11203620.
Research Keywords
- Analytical models
- heterogeneous mean-field
- hypergraph
- Internet
- Malware
- Malware propagation
- Numerical models
- Pandemics
- Topology
- wireless network
- Wireless networks
RGC Funding Information
- RGC-funded
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