Social-Aware Stateless Forwarding in Pocket Switched Networks

Several social-aware routing protocols for pocket switched networks have been recently introduced in the literature. The main idea underlying these protocols is to exploit state information (e.g., history of past encounters) to deduce information on the social structure of the network, and to optimize routing based on this information. While social-aware routing protocols have been shown to have superior performance to social-oblivious, stateless routing protocols such as, e.g., BinarySW, the improvement comes at the cost of considerable storage overhead required on the nodes, which is instead not required for stateless approaches. So, whether the benefits of social-aware routing protocols would still be present when storage capacity at the nodes is constrained is not clear. In this paper we present SANE, the first forwarding mechanism that combines the advantages of both social-aware and stateless approaches. SANE is based on the observation-that we validate on real-world traces-that individuals with similar interests tend to meet more often. In our approach, individuals (network members) are characterized by their interest profile, a compact representation of their interests. By implementing a simple interest profile similarity based forwarding rule, SANE is free of network state information, thus overcoming the storage capacity problem with existing social-aware approaches. Through extensive experiments, we show the superiority of social-aware, stateless forwarding over existing stateful, social-aware and stateless, social-oblivious routing approaches. An important byproduct of our interest-based approach is that it easily enables innovative routing primitives, such as interest-casting. An interest-casting protocol is also introduced in this paper, and extensively evaluated through experiments based on both real-world and synthetic mobility traces

Distributed Multi-authority Attribute-based Encryption Scheme for Friend Discovery in Mobile Social Networks

AbstractIn recent years, the rapid expansion of the capability of portable devices, cloud servers and cellular network technologies is the wind beneath the wing of mobile social networks. Compared to traditional web-based online social networks, the mobile social networks can assist users to easily discover and make new social interaction with others. A challenging task is to protect the privacy of the users’ profiles and communications. Existing works are mainly based on traditional cryptographic methods, such as homomorphic and group signatures, which are very computationally costly. In this paper, we propose a novel distributed multi-authority attribute-based encryption scheme to efficiently achieve privacy-preserving without additional special signatures. In addition, the proposed scheme can achieve fine-grained and flexible access control. Detailed analysis demonstrates the effectiveness and practicability of our scheme

Content Dissemination in Mobile Social Networks

Mobile social networking(MSN) has emerged as an effective platform for social network users to pervasively disseminate the contents such as news, tips, book information, music, video and so on. In content dissemination, mobile social network users receive content or information from their friends, acquaintances or neighbors, and selectively forward the content or information to others. The content generators and receivers have different motivation and requirements to disseminate the contents according to the properties of the contents, which makes it a challenging and meaningful problem to effectively disseminate the content to the appropriate users. In this dissertation, the typical content dissemination scenarios in MSNs are investigated. According to the content properties, the corresponding user requirements are analyzed. First, a Bayesian framework is formulated to model the factors that influence users behavior on streaming video dissemination. An effective dissemination path detection algorithm is derived to detect the reliable and efficient video transmission paths. Second, the authorized content is investigated. We analyze the characteristics of the authorized content, and model the dissemination problem as a new graph problem, namely, Maximum Weighted Connected subgraph with node Quota (MWCQ), and propose two effective algorithms to solve it. Third, the authorized content dissemination problem in Opportunistic Social Networks(OSNs) is studied, based on the prediction of social connection pattern. We then analyze the influence of social connections on the content acquirement, and propose a novel approach, User Set Selection(USS) algorithm, to help social users to achieve fast and accurate content acquirement through social connections

Hey, Influencer! Message Delivery to Social Central Nodes in Social Opportunistic Networks

This paper presents a new strategy to efficiently deliver messages to influencers in social opportunistic networks. An influencer node is an important node in the network with a high social centrality and, as a consequence, it can have some characteristics such as high reputation, trustfulness and credibility, that makes it an interesting recipient. Social network analysis has already been used to improve routing in opportunistic networking, but there are no mechanisms to efficiently route and deliver messages to these network influencers. The delivery strategy proposed in this article uses optimal stopping statistical techniques to choose among the different delivery candidate nodes in order to maximise the social centrality of the node chosen for delivery. For this decision process, we propose a routing-delivery strategy that takes into account node characteristics such as how central a node is in terms of its physical encounters. We show, by means of simulations based on real traces and message exchange datasets, that our proposal is efficient in terms of influencer selection, overhead, delivery ratio and latency time. With the proposed strategy, a new venue of applications for opportunistic networks can be devised and developed using the leading figure of social influencer

Effective Cloud-Based Strategies For Managing Online Reputations

Leasing computing resources are now feasible thanks to the Infrastructure as a Service (IaaS) concept made available by cloud computing. In spite of the fact that leased computing resources provide a more financially advantageous answer to the requirements of virtual networks, customers are reluctant to make use of them due to low levels of trust in these resources. Multi-tenancy is a method for reducing operating expenses by allocating a single set of computer resources to serve the needs of several users simultaneously. The fact that computer resources and communication methods are being shared gives rise to concerns over the security and integrity of the data. Since the users are anonymous, it may be difficult for a person to decide who among their neighbours can be trusted. This may make it difficult for an individual to choose a place to live. It is very necessary to have faith in the capacity of the cloud provider (CP) to match customers with dependable co-tenants. Yet, it is in the CP's best interest to make the most of the usage of the resources. So, it enables the maximum possible degree of co-tenancy, which is unaffected by the actions of the user. We provide a powerful reputation management system that pays CPs for discriminating between genuine and malicious users. This prevents resource sharing across CPs in a federated cloud environment, which is one of the goals of our system. Through a combination of theoretical and empirical research, we demonstrate that the proposed method for managing reputations is effective and legitimate