Michael Fire

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Online social networking sites have become increasingly popular over the last few years. As a result, new interdisciplinary research directions have emerged in which social network analysis methods are applied to networks containing hundreds millions of users. Unfortunately, links between individuals may be missing due to imperfect acquirement processes or(More)
In recent years, Online Social Networks (OSNs) have essentially become an integral part of our daily lives. There are hundreds of OSNs, each with its own focus and offers for particular services and functionalities. To take advantage of the full range of services and functionalities that OSNs offer, users often create several accounts on various OSNs using(More)
Many online social network (OSN) users are unaware of the numerous security risks that exist in these networks, including privacy violations, identity theft, and sexual harassment, just to mention a few. According to recent studies, many online social network users readily expose personal and private details about themselves, such as relationship status,(More)
Today’s social networks are plagued by numerous types of malicious profiles which can range from socialbots to sexual predators. We present a novel method for the detection of these malicious profiles by using the social network’s own topological features only. Reliance on these features alone ensures that the proposed method is generic enough to be applied(More)
One dimension on the Internet, which has gained great popularity in recent years are the online social networks (OSNs). Users all over the globe write, share, and publish personal information about themselves, their friends, and their workplace. In this study we present a method for infiltrating specific users in targeted organizations by using(More)
The amount of personal information involuntarily exposed by users on online social networks is staggering, as shown in recent research. Moreover, recent reports indicate that these networks are inundated with tens of millions of fake user profiles, which may jeopardize the user’s security and privacy. To identify fake users in such networks and to improve(More)
Traffic measurements, road safety studies, and surveys are required for efficient road planning and ensuring the safety of transportation. Unfortunately, these methods can be cumbersome and very expensive. In this paper we point out a source of transportation information that is based on collaborative community-based navigation applications, such as Waze.(More)
In this paper, we propose a novel method for the prediction of a person’s success in an academic course. By extracting log data from the course’s website and applying network analysis methods, we were able to model and visualize the social interactions among the students in a course. For our analysis, we extracted a variety of features by using both graph(More)
In the recent years we have seen a significant growth in the usage of online social networks. Common networks like Facebook, Twitter, Pinterest, and Linked In have become popular all over the world. In these networks users write, share, and publish personal information about themselves, their friends, and their workplace. In this study we present a method(More)
Mature social networking services are one of the greatest assets of today’s organizations. This valuable asset, however, can also be a threat to an organization’s confidentiality. Members of social networking websites expose not only their personal information, but also details about the organizations for which they work. In this paper we analyze several(More)