Geometrical Framework for Cyber Worm Propagation in Complex Computer Networks: A Theoretical Study

Mathematics

In today's digital environment, the rapid proliferation of interconnected computing systems is making computer network penetration by malicious cyber activities increasingly common as risk. The growth of interconnectedness is Because of this leading to both increased complexities of system security and greater difficulty of effective monitoring. The prevalent self-help replication of malicious computer worms typifies this threat diverse group of calculative malwares that can spread with no user involvement (Stallings, 2018). This paper presents an up-dated replicated existing theoretical setup for worm propagation in computer networks adopting a perspective of geometrical modelling. It emphasizes on the structural interpretation of their infection over their statistical behavior. This project mainly aims to understand worm infection in a new way by using structural, spatial and topological representations of network systems. That is, studying how the layout of a network influences moving and spread of malware from node to node. The new geometrical model version of the viral spread makes a point of the spatial arrangement of nodes, the level of their connectivity, the way nodes are clustered, and the geometry of transmission, so it can explain worm spread over complex network infrastructures (Barabási, 2016). Besides, it helps to see more clearly through the infected-path, and the vulnerable structures hidden in the large-scale networks. Based on the observation about propagation speed, we can conclude that the network geometry appears to be a crucial factor affecting propagation characteristic, which is, the structure topology of a network is the key factor causing the different Malware propagation scenarios. The denser and higher interconnected network will make the infection propagate in a much faster pace by the multiple connection overlap for the transmission, thereafter the infection could have a fast and wide spreading speed almost simultaneously with the process of the infection; while the modular, hierarchical and segmented network architecture would on the contrary slow down the speed and wall off the infection speed and degree remarkably owing to the indirect connection and the separation for the network cluster (Newman, 2018). Also, central nodes, bridging links, and restrictions at the boundaries contribute quite a bit to the infection path by governing the direction and location of the propagation. They function as intermediate control points that allow or hinder the flow of malicious traffic. The findings also validate worm spread as a geometrically governed expansion process that is influenced by the structural characteristics of the network. This supports geometrical modelling as a good system for cyber security analysis and network offense or defense (Schneier, 2015), In particular in the domain of system-level vulnerability and resilience.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.