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Text mining is the process to automatically infer relevant information from semantically related text documents. This technique, which has applications from business intelligence to homeland security, terrorism and crime fight, might bring noticeable privacy issues when analyzed documents contain privacy sensitive information. In this paper, we propose a framework for privacy-preserving text analysis,...
This paper presents a framework for constructing a hierarchical categorical clustering algorithm on horizontal and vertical partitioned dataset. It is assumed that data is distributed between two parties, such that for general benefits both are willing to detect the clusters on whole dataset, but for privacy concerns, they refuse to share the original datasets. To this end, we propose algorithms based...
This paper presents a novel framework for privacy aware collaborative information sharing for data classification. Data holders participating in this information sharing system, for global benefits are interested to model a classifier on whole dataset, but are ready to share their own table of data if a certain amount of privacy is guaranteed. To address this issue, we propose a privacy mechanism...
Combination of dynamic and static analysis is very effective in detecting malicious Android apps. However, dynamic analysis is hardly practiced on large scale, due to the necessary active interaction with the malicious app, which is reliable only if performed by a user on a real device. In this paper we present a framework for distributed and collaborative analysis of Android suspicious apps, which...
Attributes describing the features of subjects, objects and of the environment are used in access and usage control models to determine the right of a subject to use an object in a given environment. Hence, it is crucial for the effective enforcement of access and usage policies that authorization systems are able to promptly retrieve the values of the required attributes from the Attribute Providers...
This paper presents and model a novel general framework for privacy aware collaborative information sharing for data analysis. Collaborative information sharing systems can be cross-domain, involve different data providers which might also be competitors. For this reason, shared information may imply privacy concerns, which must be addressed, applying privacy preserving mechanisms on information before...
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