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Web Information Systems Engineering – WISE 2015

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Table of Contents

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    Book Overview
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    Chapter 1 The Influence of Client Platform on Web Page Content: Measurements, Analysis, and Implications
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    Chapter 2 Aspect and Ratings Inference with Aspect Ratings: Supervised Generative Models for Mining Hotel Reviews
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    Chapter 3 A Web-Based Application for Semantic-Driven Food Recommendation with Reference Prescriptions
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    Chapter 4 Incorporating Cohesiveness into Keyword Search on Linked Data
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    Chapter 5 Privacy-Enhancing Range Query Processing over Encrypted Cloud Databases
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    Chapter 6 Multi-Window Based Ensemble Learning for Classification of Imbalanced Streaming Data
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    Chapter 7 A Dynamic Key Length Based Approach for Real-Time Security Verification of Big Sensing Data Stream
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    Chapter 8 Detecting Internet Hidden Paid Posters Based on Group and Individual Characteristics
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    Chapter 9 A Soft Subspace Clustering Method for Text Data Using a Probability Based Feature Weighting Scheme
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    Chapter 10 Using Web Collaboration to Create New Physical Learning Objects
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    Chapter 11 A Custom Browser Architecture to Execute Web Navigation Sequences
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    Chapter 12 File Relation Graph Based Malware Detection Using Label Propagation
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    Chapter 13 Cross-Domain Collaborative Recommendation by Transfer Learning of Heterogeneous Feedbacks
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    Chapter 14 Research on Automate Discovery of Deep Web Interfaces
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    Chapter 15 Discovering Functional Dependencies in Vertically Distributed Big Data
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    Chapter 16 Semi-supervised Document Clustering via Loci
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    Chapter 17 Differentiating Sub-groups of Online Depression-Related Communities Using Textual Cues
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    Chapter 18 A New Webpage Classification Model Based on Visual Information Using Gestalt Laws of Grouping
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    Chapter 19 Extracting Records and Posts from Forum Pages with Limited Supervision
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    Chapter 20 Improving Relation Extraction by Using an Ontology Class Hierarchy Feature
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    Chapter 21 Crisis Mapping During Natural Disasters via Text Analysis of Social Media Messages
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    Chapter 22 Tweet Location Inference Based on Contents and Temporal Association
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    Chapter 23 Finding Influential Users and Popular Contents on Twitter
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    Chapter 24 Exploring Social Network Information for Solving Cold Start in Product Recommendation
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    Chapter 25 The Detection of Multiple Dim Small Targets Based on Iterative Density Clustering and SURF Descriptor
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    Chapter 26 Collaborative Content-Based Method for Estimating User Reputation in Online Forums
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    Chapter 27 Fusion of Big RDF Data: A Semantic Entity Resolution and Query Rewriting-Based Inference Approach
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    Chapter 28 Enhancing Social Recommendation with Sentiment Communities
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    Chapter 29 Trending Topics Rank Prediction
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    Chapter 30 Moving Video Mapper and City Recorder with Geo-Referenced Videos
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    Chapter 31 WebGC Gossiping on Browsers Without a Server
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    Chapter 32 Service Discovery for Spontaneous Communities in Pervasive Environments
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    Chapter 33 C3PO: A Network and Application Framework for Spontaneous and Ephemeral Social Networks
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    Chapter 34 Towards a Unified Framework for Data Cleaning and Data Privacy
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    Chapter 35 A Data Quality Framework for Customer Relationship Analytics
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    Chapter 36 Inter-rater Reliability in Determining the Types of Vegetation on Railway Trackbeds
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    Chapter 37 Reliability of Manual Assessments in Determining the Types of Vegetation on Railway Tracks
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    Chapter 38 A Comparison of Patent Classifications with Clustering Analysis
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    Chapter 39 Combination of Evaluation Methods for Assessing the Quality of Service for Express Delivery Industry
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    Chapter 40 Geographical Constraint and Temporal Similarity Modeling for Point-of-Interest Recommendation
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    Chapter 41 A Classification-Based Demand Trend Prediction Model in Cloud Computing
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    Chapter 42 Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach
  44. Altmetric Badge
    Chapter 43 Correlation-Based Deep Learning for Multimedia Semantic Concept Detection
  45. Altmetric Badge
    Chapter 44 Social Network Privacy: Issues and Measurement
Attention for Chapter 42: Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach
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Chapter title
Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach
Chapter number 42
Book title
Web Information Systems Engineering – WISE 2015
Published in
Proceedings of the ... International Conference on Web Information Systems Engineering / co-organized by City University of Hong Kong ... [et al.] ; co-sponsored by AIMtech Centre ... [et al.]. International Conference on Web Informatio..., November 2015
DOI 10.1007/978-3-319-26187-4_42
Pubmed ID
Book ISBNs
978-3-31-926186-7, 978-3-31-926187-4
Authors

Anand Kumar, Jay Ligatti, Yi-Cheng Tu

Abstract

Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Student > Postgraduate 1 10%
Student > Bachelor 1 10%
Unknown 5 50%
Readers by discipline Count As %
Computer Science 3 30%
Business, Management and Accounting 1 10%
Veterinary Science and Veterinary Medicine 1 10%
Unknown 5 50%