Understanding the computer-virus propagation is quite essential for the construction and development of anti-virus policy. While researches about the anti-virus policy have been extensively investigated, the viewpoint from sociological perspective is relatively ignored. Therefore, this paper aims to explore the dynamics of computer-virus propagation and evaluate the effectiveness of anti-virus policies through the sociological perspective.
This research constructs a virus-propagation model based on the susceptible-exposed-infective-recovered epidemic concept to simulate and explore the dynamic behavior of multipartite computer viruses through the tool of system dynamics. The effectiveness of various anti-virus policies is then evaluated via this model.
The frequency of media contact has a significant effect on the virus infection rate. The effectiveness of user self-prevention relies on the usefulness of the virus signatures. The reporting/alarm process can enhance the capability of anti-virus software company and the detected intensity of new threat. The quarantine policy can effectively reduce the spread of computer virus.
Individuals should strengthen the self-awareness of information security to reduce the negative impact. Managers should construct and implement the information security norm to regulate the behavior of staff. Anti-virus software companies should strengthen the capability of their automatic reporting/alarm mechanism to early detect the exceptional conditions and control new threats in time.
Information security management research is still in the growth phase, but it is critically important to establish the groundwork for understanding of computer viruses and the effectiveness of anti-virus policy from assorted perspectives. The major contribution of research is to explore the propagation of multipartite computer viruses and study how to prevent their destruction from the sociological and technical perspectives.
Sung, P., Ku, C. and Su, C. (2014), "Understanding the propagation dynamics of multipartite computer virus", Industrial Management & Data Systems, Vol. 114 No. 1, pp. 86-106. https://doi.org/10.1108/IMDS-04-2013-0197Download as .RIS
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