Learn More
Inspired by the similarities between human trust and physical measurements, we have proposed a trust framework for social networks, including defining new trust metrics and their combinations, which captures both human trust level and its uncertainty, while being intuitive and user friendly. Based on our trust framework, we propose several security(More)
As social networks are becoming more and more popular, more and more data are available from them. Researchers are now trying to extract useful information from these big data. One possible usage of social media is to investigate stock market. There are two major events to measure in stock market - price change and trade volume. In this paper, we firstly(More)
Internet of Things (IoT) can connect a large numberof things (or agents) through communication networks for varioustypes of applications. Like in many other applications, it isvery important for all the agents in IoT systems to collaboratewith each other following predefined protocols. In this paper, we proposed a general trust management framework aiming(More)
Trust plays a very important role in people's real lives. As online social networking becomes more and more popular nowadays, it is urgent to use trust in online communities, like Amazon.com, Epinions.com, Facebook, Twitter and so on. Unfortunately, trust links in online communities are sparse compared with the number of pairs of users. To address this(More)
In today's cloud computing platforms, more and more users are now working or collaborating in multi-cloud environment, in which collaborators, clouds, computing nodes may belong to different institutions or organizations. Those different organizations might have their own policies. Security is still a big concern in cloud computing. To help cloud vendors(More)
We propose a trust management framework based on measurement theory to infer indirect trust in online social communities using trust’s transitivity property. Inspired by the similarities between human trust and measurement, we propose a new trust metric, composed of impression and confidence, which captures both trust level and its certainty.(More)
The reliability of information in health social network sites (HSNs) is an imperative concern since false information can cause tremendous damage to health consumers. To mitigate the damages, we utilize our previous trust framework that captures both human trust level and its uncertainty. We show how our previously presented trust framework can be applied(More)
—Recommender system is currently widely used in many e-commerce systems, such as Amazon, eBay, and so on. It aims to help users to find items which they may be interested in. In literature, neighborhood-based collaborative filtering and matrix factorization are two common methods used in recommender systems. In this paper, we combine these two methods with(More)