Abstract
Online Social Networks (OSNs) are based on actual trust relationships in environments which help people communicate with friends, family and acquaintances. Malicious individuals take advantage of this trust relationship to propagate malware through social networks. We study the dynamics of malware propagation among OSN users. Social networks users are referred to as nodes which is in two compartments: Healthy (H), or Infected (I). A H node could either be susceptible to infection (S) or removed (R). Simulations were carried out in R using the EpiModel network simulation package. Two networks were simulated thrice with different parameters to give better average values. Two categories of nodes, first category comprises of 3000 nodes with fewer connections and the second category comprising of 7000 nodes are the influential nodes with more connections. The larger network tends to have a higher fraction of nodes getting infected per unit time due to the high level of connectivity, as opposed to the small network where the number of connections is few. However, the infection tends to persist in the network as long as the birth rate is not equal to zero.
Highlights
1.1 BackgroundA social network consists of individuals called nodes, connected by interdependencies such as friendship, kinship, common interest, dislike, etc
Online Social Networks (OSNs) are based on actual trust relationships in environments which help people communicate with friends, family and acquaintances
We study the dynamics of malware propagation among OSN users
Summary
A social network consists of individuals called nodes, connected by interdependencies such as friendship, kinship, common interest, dislike, etc. The structure of these networks are often represented using graphs (Kosorukoff, 2011). According to Faghani et al (2012), there are three major types of OSN malware – Cross Site Scripting (XSS) worms, Trojans and ClickJacking worms. An XSS worm self-propagates among visitors of a website with the aim of progressively infecting other visitors. Trojans like Koobface use social engineering and spread themselves in social networks by broadcasting messages with fascinating topics
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