This paper investigates ownership types in a concurrent setting using the Join calculus as the mo... more This paper investigates ownership types in a concurrent setting using the Join calculus as the model of processes. Ownership types have the effect of statically preventing certain communication, and can block the accidental or malicious leakage of secrets. Intuitively, a channel defines a boundary and forbids access to its inside from outer channels, thus preserving the secrecy of the inner
2012 IEEE 12th International Conference on Data Mining Workshops, 2012
ABSTRACT In Online Social Networks (OSNs), it can be difficult to maintain the context of a conve... more ABSTRACT In Online Social Networks (OSNs), it can be difficult to maintain the context of a conversation or action, i.e. to know what the situation is and how to act appropriately. The resulting uncertainties may lead to privacy issues. We focus on one issue Context Collision in this paper, and motivate that a first step to address this issue is to help users distinguish groups of contacts within their OSN accounts. We conducted a small user study to investigate the criteria of users grouping the people they know. We summarized our participants' strategy of labeling the groups and found that they perform the grouping mainly by their connections with others. We used these results in the design of FreeBu, a semi-automatic and interactive grouping tool, which is based on mining friend graph data for community detection and profile information for labeling.
This paper investigates ownership types in a concurrent setting using the Join calculus as the mo... more This paper investigates ownership types in a concurrent setting using the Join calculus as the model of processes. Ownership types have the effect of statically preventing certain communication, and can block the accidental or malicious leakage of secrets. Intuitively, a channel defines a boundary and forbids access to its inside from outer channels, thus preserving the secrecy of the inner
2012 IEEE 12th International Conference on Data Mining Workshops, 2012
ABSTRACT In Online Social Networks (OSNs), it can be difficult to maintain the context of a conve... more ABSTRACT In Online Social Networks (OSNs), it can be difficult to maintain the context of a conversation or action, i.e. to know what the situation is and how to act appropriately. The resulting uncertainties may lead to privacy issues. We focus on one issue Context Collision in this paper, and motivate that a first step to address this issue is to help users distinguish groups of contacts within their OSN accounts. We conducted a small user study to investigate the criteria of users grouping the people they know. We summarized our participants' strategy of labeling the groups and found that they perform the grouping mainly by their connections with others. We used these results in the design of FreeBu, a semi-automatic and interactive grouping tool, which is based on mining friend graph data for community detection and profile information for labeling.
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Papers by Dave Clarke