Results 11 - 20
of
75
Rendezvous Based Trust Propagation to Enhance Distributed Network Security
- International Journal of Security and Networks
"... Abstract—Development of network of nodes connected with their trust values and the propagation of these trust values to far away nodes are basic operations of the modern day trustworthy networks. Trust can be exploited to mitigate the security threats in wireless network. Most of the existing trust ..."
Abstract
-
Cited by 4 (0 self)
- Add to MetaCart
(Show Context)
Abstract—Development of network of nodes connected with their trust values and the propagation of these trust values to far away nodes are basic operations of the modern day trustworthy networks. Trust can be exploited to mitigate the security threats in wireless network. Most of the existing trust propagation methods are based on flooding trust information, which puts a heavy burden on wireless communication, especially in ad hoc network and sensor network. In this paper, we propose a rendezvous based trust propagation scheme. Trust requester and trust provider send out trust-request and computed-trust tickets respectively, which will meet in some common rendezvous node with certain probability. Computed-trust will then be propagated to the requester. We carry out detailed performance evaluations of our scheme. The results show that our method achieves up to 66 % overhead reduction in trust propagation compared to flood based methods. I.
A distributed method for trust-aware recommendation in social networks
, 2010
"... This paper contains the details of a distributed trust-aware recommendation system. Trust-base recommenders have received a lot of attention recently. The main aim of trust-based recommendation is to deal the problems in traditional Collaborative Filtering recom-menders. These problems include cold ..."
Abstract
-
Cited by 3 (0 self)
- Add to MetaCart
This paper contains the details of a distributed trust-aware recommendation system. Trust-base recommenders have received a lot of attention recently. The main aim of trust-based recommendation is to deal the problems in traditional Collaborative Filtering recom-menders. These problems include cold start users, vulnerability to attacks, etc.. Our pro-posed method is a distributed approach and can be easily deployed on social networks or real life networks such as sensor networks or peer to peer networks.1 1
Producing Timely Recommendations From Social Networks Through Targeted Search
"... There has been a significant increase in interest and participation in social networking websites recently. For many users, social networks are indispensable tools for sharing personal information and keeping abreast with updates by their acquaintances. While there has been research on understanding ..."
Abstract
-
Cited by 3 (0 self)
- Add to MetaCart
(Show Context)
There has been a significant increase in interest and participation in social networking websites recently. For many users, social networks are indispensable tools for sharing personal information and keeping abreast with updates by their acquaintances. While there has been research on understanding the structure and effects of social networks, research on using social networks for developing targeted referral systems are few even though this can be valuable because of the abundance of information about user preferences, activities and choices. The goal of this research is to develop agent-based referral systems that learn user preferences based on past rating activities and caters to an individual user’s interests by selectively searching the contributions posted by other users in close proximity in this user’s social
Z.: Which Links Should I Use? A VariogramBased Selection of Relationship Measures for Prediction of Node Attributes
- in Temporal Multigraphs. In: Proc. ASONAM 2013
, 2013
"... Abstract—When faced with the task of forming predictions for nodes in a social network, it can be quite difficult to decide which of the available connections among nodes should be used for the best results. This problem is further exacerbated when temporal information is available, prompting the qu ..."
Abstract
-
Cited by 3 (2 self)
- Add to MetaCart
(Show Context)
Abstract—When faced with the task of forming predictions for nodes in a social network, it can be quite difficult to decide which of the available connections among nodes should be used for the best results. This problem is further exacerbated when temporal information is available, prompting the question of whether this information should be aggregated or not, and if not, which portions of it should be used. With this challenge in mind, we propose a novel utilization of variograms for selecting potentially useful relationship types, whose merits are then evaluated using a Gaussian Conditional Random Field model for node attribute prediction of temporal social networks with a multigraph structure. Our flexible model allows for measuring many kinds of relationships between nodes in the network that evolve over time, as well as using those relationships to augment the outputs of various unstructured predictors to further improve performance. The experimental results exhibit the effec-tiveness of using particular relationships to boost performance of unstructured predictors, show that using other relationships could actually impede performance, and also indicate that while variograms alone are not necessarily sufficient to identify a useful relationship, they greatly help in removing obviously useless measures, and can be combined with intuition to identify the optimal relationships.
SocialSwarm: Exploiting Distance in Social Networks for Collaborative Flash File Distribution
"... Abstract—Social networks can serve as an effective mechanism for distribution of vulnerability patches and other malware immunization code. We propose a novel approach—SocialSwarm— by which peers exploit distances to their social peers to approximate levels of altruism and to collaborate on flash di ..."
Abstract
-
Cited by 2 (1 self)
- Add to MetaCart
(Show Context)
Abstract—Social networks can serve as an effective mechanism for distribution of vulnerability patches and other malware immunization code. We propose a novel approach—SocialSwarm— by which peers exploit distances to their social peers to approximate levels of altruism and to collaborate on flash distribution of large files. SocialSwarm supports heterogeneous BitTorrent swarms of mixed social and non-social peers. We implement SocialSwarm as an extension to the Rasterbar libtorrent library— widely used by BitTorrent clients—and evaluate it on a testbed of 500 independent clients with social distances extracted from Facebook. We show that SocialSwarm can significantly reduce the average file distribution time, not only among socially connected peers, but also among other swarm participants. I.
Proximity-Based Trust Inference for Mobile Social Networking ⋆
, 2011
"... Abstract. The growing trend to social networking and increased prevalence of new mobile devices lead to the emergence of mobile social networking applications where users are able to share experience in an impromptu way as they move. However, this is at risk for mobile users since they may not have ..."
Abstract
-
Cited by 2 (0 self)
- Add to MetaCart
(Show Context)
Abstract. The growing trend to social networking and increased prevalence of new mobile devices lead to the emergence of mobile social networking applications where users are able to share experience in an impromptu way as they move. However, this is at risk for mobile users since they may not have any knowledge about the users they socially connect with. Trust management then appears as a promising decision support for mobile users in establishing social links. However, while the literature is rich of trust models, most approaches lack appropriate trust bootstrapping, i.e., the initialization of trust values. This paper addresses this challenge by introducing proximity-based trust initialization based on the users ’ behavioral data available from their mobile devices or other types of social interactions. The proposed approach is further assessed in the context of mobile social networking using users behavioral data collected by the MIT reality mining project. Results show that the inferred trust values correlate with the self-report survey of users relationships. Key words: Trust bootstrapping, mobile social network, small worlds 1
Enhancing Participation Process in Public Decision Making with MCDA and Trust Modeling
- International Journal of Computer Science Issues
, 2011
"... Multi-criteria decision analysis provides an effective and valuable method of articulating and structuring deliberations within public participation. Public participation means that citizens are involved in the public decision making that has an effect on them. In order to encourage participation wh ..."
Abstract
-
Cited by 2 (2 self)
- Add to MetaCart
(Show Context)
Multi-criteria decision analysis provides an effective and valuable method of articulating and structuring deliberations within public participation. Public participation means that citizens are involved in the public decision making that has an effect on them. In order to encourage participation while integrating the deliberative perspectives from various participants in public sector, we should support the participatory public decision making process. Our effort is oriented towards integrating trust-based multi-agent modeling within multi-criteria group decision support systems. Decision makers are modeled as agents and each agent has a role in decision making processes which identified by trust level. In this paper, we propose a framework and model to enhance the success of participation process in participatory public decision making. A simple example is also presented in this paper to give a clarity how the framework and model can be implemented in the real situation.
Recurrent Neural Network Based Language Model Personalization by Social Network Crowdsourcing
"... Speech recognition has become an important feature in smartphones in recent years. Different from traditional au-tomatic speech recognition, the speech recognition on smart-phones can take advantage of personalized language models to model the linguistic patterns and wording habits of a particu-lar ..."
Abstract
-
Cited by 2 (0 self)
- Add to MetaCart
(Show Context)
Speech recognition has become an important feature in smartphones in recent years. Different from traditional au-tomatic speech recognition, the speech recognition on smart-phones can take advantage of personalized language models to model the linguistic patterns and wording habits of a particu-lar smartphone owner better. Owing to the popularity of social networks in recent years, personal texts and messages are no longer inaccessible. However, data sparseness is still an un-solved problem. In this paper, we propose a three-step adapta-tion approach to personalize recurrent neural network language models (RNNLMs). We believe that its capability to model word histories as distributed representations of arbitrary length can help mitigate the data sparseness problem. Furthermore, we also propose additional user-oriented features to empower the RNNLMs with stronger capabilities for personalization. The experiments on a Facebook dataset showed that the proposed method not only drastically reduced the model perplexity in preliminary experiments, but also moderately reduced the word error rate in n-best rescoring tests.
