Abstract
Multi-user computer environments pose potential threats to users data in organisations, in that unauthorised subsequent users who log on to the same computer could leak, alter or delete data belonging to users who previously logged in to the same computer. Such a threat is inspired by Locard's exchange principle, which states (in its digital form) that every interaction with a system must ultimately leave some trace, and as a result, such trace could carry with it sensitive information that subsequent interactions may obtain without authorisation. Therefore, we attempt in this paper to define a subsequent users analysis that calculates this potential loss in data security based on data visibility and sensitivity values. We outline how such analysis can be used in the real world to enhance decision making process when logging in to a shared computer. We adopt a data-driven approach in defining our analysis and we demonstrate the validity of the analysis over a large open Cybersecurity dataset, which associates users with computers.
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