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A Survey of Quantification of Privacy Preserving Data Mining Algorithms
TLDR
This chapter reviews and summarizes existing criteria and metrics in evaluating privacy preserving techniques and provides a comprehensive view on a set of metrics related to existing privacy preserving algorithms so that researchers can gain insights on how to design more effective measurement and PPDM algorithms.
An Approach to Evaluate Data Trustworthiness Based on Data Provenance
TLDR
A data provenance trust model is proposed which takes into account various factors that may affect the trustworthiness and, based on these factors, assigns trust scores to both data and data providers.
MoZo: A Moving Zone Based Routing Protocol Using Pure V2V Communication in VANETs
TLDR
This work proposes a novel approach that introduces moving object modeling and indexing techniques from the theory of large moving object databases into the design of VANET routing protocols and demonstrates the superiority of this approach compared with both clustering and non-clustering based routing protocols.
A Brokerage-Based Approach for Cloud Service Selection
TLDR
A novel brokerage-based architecture in the Cloud is proposed, where the Cloud brokers is responsible for the service selection and a unique indexing technique for managing the information of a large number of Cloud service providers is designed.
EXAM: a comprehensive environment for the analysis of access control policies
TLDR
The proposed policy analyzer combines the advantages of existing MTBDD-based and SAT-solver-based techniques and supports various types of analysis query, which are categorized in the paper.
iPrivacy: Image Privacy Protection by Identifying Sensitive Objects via Deep Multi-Task Learning
TLDR
This paper consists of the following contributions: massive social images and their privacy settings are leveraged to learn the object-privacy relatedness effectively and identify a set of privacy-sensitive object classes automatically and a deep multi-task learning algorithm is developed.
Access control policy combining: theory meets practice
TLDR
A policy combining language PCL, which can succinctly and precisely express a variety of PCAs, which is based on automata theory and linear constraints, and is more expressive than existing approaches.
Continuous Clustering of Moving Objects
TLDR
An extensive experimental study shows that the new scheme performs significantly faster than traditional ones that frequently rebuild clusters and is effective in preserving the quality of moving-object clusters.
An algebra for fine-grained integration of XACML policies
TLDR
An algebra for fine-grained integration of sophisticated policies of collaborating parties, which consists of three binary and two unary operations, is able to support the specification of a large variety of integration constraints.
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