Browsing by Author "Mohaisen, Abedelaziz"
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Item Keep your friends close: Incorporating trust into social network-based Sybil defenses(2010-08-24) Mohaisen, Abedelaziz; Hopper, Nicholas J.; Kim, YongdaeSocial network-based Sybil defenses exploit the algorithmic properties of social graphs to infer the extent to which an arbitrary node in such a graph should be trusted. However, these systems do not consider the different amounts of trust represented by different graphs, and different levels of trust between nodes, though trust is a crucial requirement in these systems. For instance, co-authors in an academic collaboration graph are trusted in a different manner than social friends. Furthermore, some social friends are more trusted than others. However, previous designs for social network-based Sybil defenses have not considered the inherent trust properties of the graphs they use. In this paper we introduce several designs to tune the performance of Sybil defenses by accounting for differential trust in social graphs and modeling these trust values by biasing random walks performed on these graphs. Surprisingly, we find that the cost function, the required length of random walks to accept all honest nodes with overwhelming probability, is much greater in graphs with high trust values, such as co-author graphs, than in graphs with low trust values such as online social networks. We show that this behavior is due to the greater number of close-knit communities in high-trust graphs, requiring longer walk to traverse multiple communities. Furthermore, we show that our proposed designs to account for trust increase the cost function of graphs with low trust value.Item SocialCloud: Using Social Networks for Building Distributed Computing Services(2011-12-08) Mohaisen, Abedelaziz; Tran, Huy; Chandra, Abhishek; Kim, YongdaeIn this paper we investigate a new computing paradigm, called SocialCloud, in which computing nodes are governed by social ties driven from a bootstrapping trust-possessing social graph. We investigate how this paradigm differs from existing computing paradigms, such as grid computing and the conventional cloud computing paradigms. We show that incentives to adopt this paradigm are intuitive and natural, and security and trust guarantees provided by it are solid. We propose metrics for measuring the utility and advantage of this computing paradigm, and using real-world social graphs and structures of social traces; we investigate the potential of this paradigm for ordinary users. We study several design options and trade-offs, such as scheduling algorithms, centralization, and straggler handling, and show how they affect the utility of the paradigm. Interestingly, we conclude that whereas graphs known in the literature for high trust properties do not serve distributed trusted computing algorithms, such as Sybil defenses---for their weak algorithmic properties, such graphs are good candidates for our paradigm for their self-load-balancing features.Item Towards trustworthy computing on social networks: measurements and new applications.(2012-08) Mohaisen, AbedelazizIn this work we study social networks by measurements and verification of assumption widely and blindly used for building security and communication services on top of these networks. We measure the mixing time---a major property used for building trustworthy systems on social networks, the expansion, and the betweenness in social graphs. We show that some of these properties do not hold, whereas others hold with less quality than assumed in the literature. From there, we propose to proceed to study these properties in different settings. We propose to study one of these widely properties, the mixing time, under several conditions used widely as practices for modifying social graphs: graph sampling and omission of graph directions. We explore reasons behind the quality of the mixing time, and propose several heuristics to improve it. Motivated by the lack of work on accounting for differential trust in social network-based applications---Sybil defenses in particular, we develop four designs and use them to account for trust in a benchmark technique of Sybil defense (SybilLimit). We show empirically that our designs improve the security of this defense at some reasonable cost. We propose to extend these algorithms to other applications, Sybil defenses as well as other routing and information dissemination applications on top of social networks and rely on trust and social graphs' structure in their operation. Finally, we use social networks for building two types of applications that make use of new properties discovered in these networks. The first application is a distributed computing service (called socialcloud) that does not make any direct use of a global property of social graphs (such as the mixing time or the expansion). We show that nodes in socialcloud finish computing tasks relatively quickly even when as much as 30% of the nodes in the system are outsourcing computations. The second system we design is DynaMix, an anonymous communication service that incorporates dynamics in the social graph for anonymity. We show that dynamics of these networks can be used to improve anonymity of users.