Your search for: 'author:("Elovici, Yuval")' has returned 2 results. (0.099s) Save search

Authors: Puzis, Rami | Elovici, Yuval | Dolev, Shlomi

Article Type: Research Article

Abstract: In many applications we are required to locate the most prominent group of vertices in a complex network. Group Betweenness Centrality can be used to evaluate the prominence of a group of vertices. Evaluating the Betweenness of every possible group in order to find the most prominent is not computationally feasible for large networks. In this paper we present two algorithms for finding the most prominent group. The first algorithm is based on heuristic search and the second is based on iterative greedy choice of vertices. The algorithms were evaluated on random and scale-free networks. Empirical evaluation suggests that the …greedy algorithm results were negligibly below the optimal result. In addition, both algorithms performed better on scale-free networks: heuristic search was faster and the greedy algorithm produced more accurate results. The greedy algorithm was applied for optimizing deployment of intrusion detection devices on network service provider infrastructure. Show more

Keywords: Complex networks, group betweenness centrality, heuristic search

Citation: AI Communications, vol. 20, no. 4, pp. 287-296, 2007

Authors: Elyashar, Aviad | Fire, Michael | Kagan, Dima | Elovici, Yuval

Article Type: Research Article

Abstract: A dimension of the Internet that has gained great popularity in recent years is the platform of online social networks (OSNs). Users all over the world write, share, and publish personal information about themselves, their friends, and their workplaces within this platform of communication. In this study we demonstrate the relative ease of creating malicious socialbots that act as social network “friends”, resulting in OSN users unknowingly exposing potentially harmful information about themselves and their places of employment. We present an algorithm for infiltrating specific OSN users who are employees of targeted organizations, using the topologies of organizational social networks …and utilizing socialbots to gain access to these networks. We focus on two well-known OSNs – Facebook and Xing – to evaluate our suggested method for infiltrating key-role employees in targeted organizations. The results obtained demonstrate how adversaries can infiltrate social networks to gain access to valuable, private information regarding employees and their organizations. Show more

Keywords: Socialbots, social networks security and privacy, organization mining, Facebook, Xing

DOI: 10.3233/AIC-140650

Citation: AI Communications, vol. 29, no. 1, pp. 87-106, 2016