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NaEPASC: a novel and efficient public auditing scheme for cloud data

期刊名称：Journal of Zhejiang University SCIENCE C
时间：2014.9.23
页码：794-804
分类：TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
作者机构：[1]College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China, [2]School of Computer Science, National University of Defense Technology, Changsha 410073, China
相关基金：Project supported by the National Natural Science Foundation of China （Nos. 60933005 and 91124002）, the National High-Tech R＆D Program （863） of China （Nos. 012505, 2011AA010702, 2012AA01A401, and 2012AA01A402）, the 242 Information Se- curity Program （No. 2011A010）, and the National Science and Technology Support Program （Nos. 2012BAH38B04 and 2012BAH38B06）, China
相关项目：非常规突发事件在线应急感知、预警与危机情报导航的社会计算方法

作者： Shuang Tan|Yan Jia|

中文摘要：

Message forwarding (e.g.,retweeting on Twitter.com) is one of the most popular functions in many existing microblogs,and a large number of users participate in the propagation of information,for any given messages.While this large number can generate notable diversity and not all users have the same ability to diffuse the messages,this also makes it challenging to find the true users with higher spreadability,those generally rated as interesting and authoritative to diffuse the messages.In this paper,a novel method called SpreadRank is proposed to measure the spreadability of users in microblogs,considering both the time interval of retweets and the location of users in information cascades.Experiments were conducted on a real dataset from Twitter containing about 0.26 million users and 10 million tweets,and the results showed that our method is consistently better than the PageRank method with the network of retweets and the method of retweetNum which measures the spreadability according to the number of retweets.Moreover,we find that a user with more tweets or followers does not always have stronger spreadability in microblogs.

英文摘要：

Message forwarding （e.g., retweeting on Twitter.corn） is one of the most popular functions in many existing microblogs, and a large number of users participate in the propagation of information, for any given messages. While this large number can generate notable diversity and not all users have the same ability to diffuse the messages, this also makes it challenging to find the true users with higher spreadability, those generally rated as interesting and authoritative to diffuse the messages. In this paper, a novel method called SpreadRank is proposed to measure the spreadability of users in microblogs, considering both the time interval of retweets and the location of users in information cascades. Experiments were conducted on a real dataset from Tvitter containing about 0.26 million users and10 million tweets, and the results showed that our method is consistently better than the PageRank method with the network of retweets and the method of retweetNum which measures the spreadability according to the number of retweets. Moreover, we find that a user with more tweets or followers does not always have stronger spreadability in microblogs.

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