Name
Abstract | ||
|---|---|---|
The propagation approach of a botnet largely dictates its formation, establishing a foundation of bots for future exploitation. The chosen propagation method determines the attack surface and, consequently, the degree of network penetration, as well as the overall size and the eventual attack potency. It is therefore essential to understand propagation behaviours and influential factors in order to better secure vulnerable systems. Whilst botnet propagation is generally well studied, newer technologies like IoT have unique characteristics which are yet to be thoroughly explored. In this paper, we apply the principles of epidemic modelling to IoT networks consisting of wireless sensor nodes. We build IoT-SIS, a novel propagation model which considers the impact of IoT-specific characteristics like limited processing power, energy restrictions, and node density on the formation of a botnet. Focusing on worm-based propagation, this model is used to explore the dynamics of spread using numerical simulations and the Monte Carlo method to discuss the real-life implications of our findings. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1155/2019/3745619 | SECURITY AND COMMUNICATION NETWORKS |
Field | DocType | Volume |
Monte Carlo method,Attack surface,Wireless,Botnet,Computer science,Internet of Things,Computer network,Malware,Wireless sensor network | Journal | 2019 |
ISSN | Citations | PageRank |
1939-0114 | 1 | 0.35 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dilara Acarali | 1 | 8 | 0.87 |
| Muttukrishnan Rajarajan | 2 | 593 | 61.50 |
| Nikos Komninos | 3 | 208 | 16.34 |
| Bruno Bogaz Zarpelão | 4 | 98 | 10.59 |