Abstract. This paper introduces a Context-aware Privacy Policy Language (CPPL) that enables mobile users to control who can access their context information, at what detail, and in which situation by specifying their contextaware privacy rules. Context-aware privacy rules map a set of privacy rules to one or more user's situations, in which these rules are valid. Each time a user's situation changes, a list of valid rules is updated, leaving only a subset of the specified rules to be evaluated by a privacy framework upon arrival of a context query. In the existing context-dependent privacy policy languages a user's context is used as an additional condition parameter in a privacy rule, thus all the specified privacy rules have to be evaluated when a request to access a user's context arrives. Keeping the number of rules that need to be evaluated small is important because evaluation of a large number of privacy rules can potentially increase the response time to a context query. CPPL also enables rules to be defined based on a user's social relationship with a context requestor, which reduces the number of rules that need to be defined by a user and that consequently need to be evaluated by a privacy mechanism. This paper shows that when compared to the existing context-dependent privacy policy languages, this number of rules (that are encoded using CPPL) decreases with an increasing number of user-defined situations and requestors that are represented by a small number of social relationship groups.
For instance, Behrooz et al. REF proposed a context-aware privacy policy language (CPPL) that uses context to pre-filter policies applicable to the current situation, in order to reduce the number of policies that actually have to be evaluated.
A Context-Aware Privacy Policy Language for Controlling Access to Context Information of Mobile Users
MobiSec
Computer Science