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Displaying 1-22 out of 22 total
A Spectrum-Based Framework for Quantifying Randomness of Social Networks
Found in: IEEE Transactions on Knowledge and Data Engineering
By Xiaowei Ying,Leting Wu,Xintao Wu
Issue Date:December 2011
pp. 1842-1856
Social networks tend to contain some amount of randomness and some amount of nonrandomness. The amount of randomness versus nonrandomness affects the properties of a social network. In this paper, we theoretically analyze graph randomness and present a fra...
Examining Multi-factor Interactions in Microblogging Based on Log-linear Modeling
Found in: 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
By Zhilin Luo, Xintao Wu, Wandong Cai, Dong Peng
Issue Date:August 2012
pp. 189-193
Microblogging, as a new form of social media, attracts a huge number of users and becomes very popular. In this paper, we consider a fundamental social network issue that illustrates how information flows through a social media network and specify why user...
On Learning Cluster Coefficient of Private Networks
Found in: 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
By Yue Wang, Xintao Wu, Jun Zhu, Yang Xiang
Issue Date:August 2012
pp. 395-402
Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering coefficient or modularity often have high sensitivity, which is different from traditional aggregate functi...
Generating program inputs for database application testing
Found in: Automated Software Engineering, International Conference on
By Kai Pan,Xintao Wu,Tao Xie
Issue Date:November 2011
pp. 73-82
Testing is essential for quality assurance of database applications. Achieving high code coverage of the database application is important in testing. In practice, there may exist a copy of live databases that can be used for database application testing. ...
Spectrum based fraud detection in social networks
Found in: Data Engineering, International Conference on
By Xiaowei Ying,Xintao Wu,Daniel Barbara
Issue Date:April 2011
pp. 912-923
Social networks are vulnerable to various attacks such as spam emails, viral marketing and the such. In this paper we develop a spectrum based detection framework to discover the perpetrators of these attacks. In particular, we focus on Random Link Attacks...
On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing
Found in: Data Mining Workshops, International Conference on
By Ling Guo, Xiaowei Ying, Xintao Wu
Issue Date:December 2010
pp. 466-473
Privacy preserving micro data publication has received wide attentions. In this paper, we investigate the randomization approach and focus on attribute disclosure under linking attacks. We give efficient solutions to determine optimal distortion parameters...
A Mutual Authentication Model between Merchant and Consumer in M-Commerce
Found in: Innovative Computing ,Information and Control, International Conference on
By Mingqiu Song, Jiahua Li, Xintao Wu
Issue Date:September 2007
pp. 489
In this paper, a mutual authentication model for m- commerce payment is proposed. Its key differentia from the existing protocols involving trusted third party in M-commerce is its characteristics of minimality, manageability, and Single Sign-On. As micro-...
Deriving Private Information from Perturbed Data Using IQR Based Approach
Found in: Data Engineering Workshops, 22nd International Conference on
By Songtao Guo, Xintao Wu, Yingjiu Li
Issue Date:April 2006
pp. 92
Several randomized techniques have been proposed for privacy preserving data mining of continuous data. These approaches generally attempt to hide the sensitive data by randomly modifying the data values using some additive noise and aim to reconstruct the...
Privacy Aware Data Generation for Testing Database Applications
Found in: Database Engineering and Applications Symposium, International
By Xintao Wu, Chintan Sanghvi, Yongge Wang, Yuliang Zheng
Issue Date:July 2005
pp. 317-326
Testing of database applications is of great importance. A significant issue in database application testing consists in the availability of representative data. In this paper we investigate the problem of generating a synthetic database based on a-priori ...
GenExplore: Interactive Exploration of Gene Interactions from Microarray Data
Found in: Data Engineering, International Conference on
By Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liying Zhang
Issue Date:April 2004
pp. 860
DNA Microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that show similar expression patterns. However, this approach usually fails to unveil...
Compressing High Dimensional Datasets by Fractals
Found in: Data Compression Conference
By Xintao Wu, Daniel Barbará
Issue Date:March 2003
pp. 452
No summary available.
Using aggregate human genome data for individual identification
Found in: 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
By Yue Wang,Xintao Wu,Xinghua Shi
Issue Date:December 2013
pp. 410-415
Data privacy in genome-wide association studies (GWAS) is a critical yet under-exploited research area. In this paper, we first provide a method to construct a two-layered bayesian network explicitly revealing the conditional dependency between SNPs and tr...
Spectrum-Based Network Visualization for Topology Analysis
Found in: IEEE Computer Graphics and Applications
By Xianlin Hu, Aidong Lu, Xintao Wu
Issue Date:January 2013
pp. 58-68
Network visualization techniques have been widely used to explore social networks, which are crucial to many application domains. A proposed visual-analytics approach provides functions that were previously hard to obtain. Based on recent achievements in s...
An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy
Found in: Data Mining Workshops, International Conference on
By Ling QIU, Yingjiu LI, Xintao WU
Issue Date:December 2006
pp. 551-558
Data mining is playing an important role in decision making. It is beneficial to outsource data mining tasks if an organization does not have required expertise in-house. However, the organization may lose business intelligence and customer privacy during ...
Guided test generation for database applications via synthesized database interactions
Found in: ACM Transactions on Software Engineering and Methodology (TOSEM)
By Kai Pan, Tao Xie, Xintao Wu
Issue Date:March 2014
pp. 1-27
Testing database applications typically requires the generation of tests consisting of both program inputs and database states. Recently, a testing technique called Dynamic Symbolic Execution (DSE) has been proposed to reduce manual effort in test generati...
Database state generation via dynamic symbolic execution for coverage criteria
Found in: Proceedings of the Fourth International Workshop on Testing Database Systems (DBTest '11)
By Kai Pan, Tao Xie, Xintao Wu
Issue Date:June 2011
pp. 1-6
Automatically generating sufficient database states is imperative to reduce human efforts in testing database applications. Complementing the traditional block or branch coverage, we develop an approach that generates database states to achieve advanced co...
Interactive detection of network anomalies via coordinated multiple views
Found in: Proceedings of the Seventh International Symposium on Visualization for Cyber Security (VizSec '10)
By Aidong Lu, Lane Harrison, Weichao Wang, Xianlin Hu, Xiaowei Ying, Xintao Wu
Issue Date:September 2010
pp. 91-101
This paper presents a new approach to intrusion detection that supports the identification and analysis of network anomalies using an interactive coordinated multiple views (CMV) mechanism. A CMV visualization consisting of a node-link diagram, scatterplot...
Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing
Found in: Proceedings of the 3rd Workshop on Social Network Mining and Analysis (SNA-KDD '09)
By Kai Pan, Ling Guo, Xiaowei Ying, Xintao Wu
Issue Date:June 2009
pp. 1-10
Many applications of social networks require identity and/or relationship anonymity due to the sensitive, stigmatizing, or confidential nature of user identities and their behaviors. Recent work showed that the simple technique of anonymizing graphs by rep...
On the use of spectral filtering for privacy preserving data mining
Found in: Proceedings of the 2006 ACM symposium on Applied computing (SAC '06)
By Songtao Guo, Xintao Wu
Issue Date:April 2006
pp. 622-626
Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining. The previous work based on spectral filtering, show the noise may be separated from the perturbed data under some conditions and as a result ...
Towards value disclosure analysis in modeling general databases
Found in: Proceedings of the 2006 ACM symposium on Applied computing (SAC '06)
By Songtao Guo, Xintao Wu, Yingjiu Li
Issue Date:April 2006
pp. 617-621
The issue of confidentiality and privacy in general databases has become increasingly prominent in recent years. A key element in preserving privacy and confidentiality of sensitive data is the ability to evaluate the extent of all potential disclosure for...
Privacy preserving database application testing
Found in: Proceedings of the 2003 ACM workshop on Privacy in the electronic society (WPES '03)
By Xintao Wu, Yongge Wang, Yuliang Zheng
Issue Date:October 2003
pp. 118-128
Traditionally, application software developers carry out their tests on their own local development databases. However, such local databases usually have only a small number of sample data and hence cannot simulate satisfactorily a live environment, especi...
B-EM: a classifier incorporating bootstrap with EM approach for data mining
Found in: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '02)
By Jianping Fan, Kalpathi R. Subramanian, Xintao Wu
Issue Date:July 2002
pp. 670-675
This paper investigates the problem of augmenting labeled data with unlabeled data to improve classification accuracy. This is significant for many applications such as image classification where obtaining classification labels is expensive, while large un...