In many applications we are required to increase the deployment of a distributed monitoring system on an evolving network. In this paper we present a new method for finding candidate locations for additional deployment in the network. This method is based on the Group Betweenness Centrality (GBC) measure that is used to estimate the influence of a group of nodes over the information flow in the network. The new method assists in finding the location of k additional monitors in the evolving network, such that the portion of additional traffic covered is at least (1 − 1/e) of the optimal.
Modern business activities rely on extensive email exchange. Email "wrong recipients" mistakes have become widespread, and the severe damage caused by such mistakes constitutes a disturbing problem both for organizations and for individuals. Various solutions attempt to analyze email exchange for preventing emails to be sent to wrong recipients. However there is still no satisfying solution: many email addressing mistakes are not detected and in many cases correct recipients are wrongly marked as potential addressing mistake.In this paper we present a new approach for preventing emails "slip-ups" in organizations. The approach is based on analysis of emails exchange among members of the organization and identification of groups of members that exchange emails with common topics. Each member"s topics are then used during the enforcement phase for detecting potential leakage. When a new email is composed and about to be sent, each email recipient is analyzed. A recipient is approved if the email"s content belongs to at least one of the topics common to the sender and the recipient.We evaluated the new approach by comparing its detection performance to a baseline approach using the Enron Email dataset. Our evaluation results suggests that group communication analysis improves the performance of a baseline email classifier, which classifies a new email based only on emails exchanged in the past between the sender of the email and each of the recipients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.