John Alexander Wells Fargo
This paper will discuss a specific analysis of desktop-based virus alerts conducted within our company, and some of the conclusions that were drawn from it. We were interested in knowing what made some users more likely than other users to encounter a virus.
These are the questions we started with, but these quickly led to others as the implications of our findings opened new topics of discussion. Indeed, the very definition of `squeak' itself became a very meaningful metric.
As this paper describes the analysis process we followed, it will attempt to generalize the techniques and issues for use by other domains. It will discuss the construction of a vendor-independent metric for the health of a domain based on desktop alerting, and how to classify users into infection rate populations based upon their relative frequency of anti-virus detection alerts. This will then be followed with a discussion of how to identify shifts in user populations and infection trends over time.
In conclusion, this paper will touch on how this type of analysis can be used to shape the communication process within your environment, as well as how to manage your helpdesk response resources more efficiently.
