We consider the problem of detecting clones in wireless mobile adhoc networks. We assume that one of the devices of the network has been cloned. Everything, including certificates and secret keys. This can happen quite easily, because of a virus that immediately after sending all the content of the infected device to the adversary destroys itself, or just because the owner has left his device unattended for a few minutes in a hostile environment. The problem is to detect this attack. We propose a solution in networks of mobile devices carried by individuals. These networks are composed by nodes that have the capability of using short-range communication technology like blue-tooth or Wi-Fi, where nodes are carried by mobile users, and where links appear and disappear according to the social relationships between the users. Our idea is to use social physical contacts, securely collected by wireless personal smart-phones, as a biometric way to authenticate the legitimate owner of the device and detect the clone attack. We introduce two mechanisms: Personal Marks and Community Certificates. Personal Marks is a simple cryptographic protocol that works very well when the adversary is an insider, a malicious node in the network that is part, or not very far, from the social community of the original device that has been cloned. Community Certificates work very well when the adversary is an outsider, a node that has the goal of using the stolen credentials when interacting with other nodes that are far in the social network from the original device. When combined, these mechanisms provide an excellent protection against this very strong attack. We prove our ideas and solutions with extensive simulations in a real world scenario-with mobility traces collected in a real life experiment
The idea of exploiting information regarding social ties between nodes is not new, actually it is common to a good part of the literature on pocket switched networks (PSN) and similar social networks. Much research has been dedicated to the analysis of the data collected during real-life experiments, to compute statistical properties of human mobility, and to uncover its structure in sub-communities @cite_16 @cite_18 @cite_37 @cite_11 @cite_30 @cite_33 @cite_36 . Later on, most of the work in the field focused on message forwarding and to find the best strategy to relay messages in order to route them to destination as fast as possible (see @cite_31 @cite_34 @cite_14 , among many others). Also security problematics such as node capture @cite_1 or selfishness @cite_5 @cite_24 have been solved by making use of social relationships among nodes.
@cite_30 @cite_18 @cite_37 @cite_14 @cite_33 @cite_36 @cite_1 @cite_34 @cite_24 @cite_5 @cite_31 @cite_16 @cite_11
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The increasing penetration of smart devices with networking capability form novel networks. Such networks, also referred as pocket switched networks (PSNs), are intermittently connected and represent a paradigm shift of forwarding data in an ad hoc manner. The social structure and interaction of users of such devices dictate the performance of routing protocols in PSNs. To that end, social information is an essential metric for designing forwarding algorithms for such types of networks. Previous methods relied on building and updating routing tables to cope with dynamic network conditions. On the downside, it has been shown that such approaches end up being cost ineffective due to the partial capture of the transient network behavior. A more promising approach would be to capture the intrinsic characteristics of such networks and utilize them in the design of routing algorithms. In this paper, we exploit two social and structural metrics, namely centrality and community, using real human mobility traces. The contributions of this paper are two-fold. First, we design and evaluate BUBBLE, a novel social-based forwarding algorithm, that utilizes the aforementioned metrics to enhance delivery performance. Second, we empirically show that BUBBLE can substantially improve forwarding performance compared to a number of previously proposed algorithms including the benchmarking history-based PROPHET algorithm, and social-based forwarding SimBet algorithm. Pocket Switched Networks (PSN) make use of both human mobility and local global connectivity in order to transfer data between mobile users' devices. This falls under the Delay Tolerant Networking (DTN) space, focusing on the use of opportunistic networking. One key problem in PSN is in designing forwarding algorithms which cope with human mobility patterns. We present an experiment measuring forty-one humans' mobility at the Infocom 2005 conference. The results of this experiment are similar to our previous experiments in corporate and academic working environments, in exhibiting a power-law distrbution for the time between node contacts. We then discuss the implications of these results on the design of forwarding algorithms for PSN. In this paper we seek to improve our understanding of human mobility in terms of social structures, and to use these structures in the design of forwarding algorithms for Pocket Switched Networks (PSNs). Taking human mobility traces from the real world, we discover that human interaction is heterogeneous both in terms of hubs (popular individuals) and groups or communities. We propose a social based forwarding algorithm, BUBBLE, which is shown empirically to improve the forwarding efficiency significantly compared to oblivious forwarding schemes and to PROPHET algorithm. We also show how this algorithm can be implemented in a distributed way, which demonstrates that it is applicable in the decentralised environment of PSNs. Applications involving the dissemination of information directly relevant to humans (e.g., service advertising, news spreading, environmental alerts) often rely on publish-subscribe, in which the network delivers a published message only to the nodes whose subscribed interests match it. In principle, publish- subscribe is particularly useful in mobile environments, since it minimizes the coupling among communication parties. However, to the best of our knowledge, none of the (few) works that tackled publish-subscribe in mobile environments has yet addressed intermittently-connected human networks. Socially-related people tend to be co-located quite regularly. This characteristic can be exploited to drive forwarding decisions in the interest-based routing layer supporting the publish-subscribe network, yielding not only improved performance but also the ability to overcome high rates of mobility and long-lasting disconnections. In this paper we propose SocialCast, a routing framework for publish-subscribe that exploits predictions based on metrics of social interaction (e.g., patterns of movements among communities) to identify the best information carriers. We highlight the principles underlying our protocol, illustrate its operation, and evaluate its performance using a mobility model based on a social network validated with real human mobility traces. The evaluation shows that prediction of colocation and node mobility allow for maintaining a very high and steady event delivery with low overhead and latency, despite the variation in density, number of replicas per message or speed.