Book ChapterDOI
Proposed Use of Information Dispersal Algorithm in User Profiling
Bhushan S. Atote,Saniya Zahoor,Mangesh Bedekar,Suja S. Panicker +3 more
- pp 77-86
TLDR
The algorithm for privacy and security purpose of different profiles, with the integration of Information Dispersal Algorithm is proposed, which would be achieved by the use of the private cloud.Abstract:
For recommending the best result to the user as per his requirement, User Profiling plays an important role. In user profiling, the profiles are created from the past data of same user. Maintaining the security and privacy of this data becomes a big challenge for researchers. Here, we are proposing the algorithm for privacy and security purpose of different profiles, with the integration of Information Dispersal Algorithm. The use of vast data of profiles by the user from any location at any time would be achieved by the use of the private cloud. As the profiles of different devices are maintained on the central cloud server, the recommendation for user for particular device can be executed easily.read more
Citations
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DeepSeq: learning browsing log data based personalized security vulnerabilities and counter intelligent measures
TL;DR: This paper has shown how simple browsing log data can jeopardize the identity and the personal integrity of a person along with analysis of preventive measures to protect them.
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Investigating the Impact of Data Analysis and Classification on Parametric and Nonparametric Machine Learning Techniques: A Proof of Concept
TL;DR: In this paper, the performance of four popular machine learning classification algorithms (Naive Bayes, decision trees, logistic regression, and random forest) on two popular benchmarked datasets (wine quality dataset and glass identification dataset) is compared.
References
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Proceedings ArticleDOI
Data Security and Privacy Protection Issues in Cloud Computing
Deyan Chen,Hong Zhao +1 more
TL;DR: This paper provides a concise but all-round analysis on data security and privacy protection issues associated with cloud computing across all stages of data life cycle and describes future research work about dataSecurity and privacy Protection issues in cloud.
Journal ArticleDOI
Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems
TL;DR: This article analyzes the privacy risks associated with several current and prominent personalization trends, namely social-based personalization, behavioral profiling, and location-basedpersonalization, and surveys user attitudes towards privacy and personalization.
Posted Content
Contextual Gaps: Privacy Issues on Facebook
TL;DR: This work analyzes two of Facebooks more recent features, Applications and News Feed, from the perspective enabled by Helen Nissenbaum’s treatment of privacy as “contextual integrity,” finding that many of the privacy issues on Facebook are primarily design issues, which could be ameliorated by an interface that made the flows of information more transparent to users.
Journal ArticleDOI
Contextual gaps: privacy issues on Facebook
TL;DR: In this paper, the authors analyze two of Facebook's more recent features, Applications and News Feed, from the perspective enabled by Helen Nissenbaum's treatment of privacy as "contextual integrity".
Book ChapterDOI
Scrutable adaptation: because we can and must
TL;DR: The paper illustrates PLUS in terms of its existing, implemented elements as well as some examples of applications built upon this approach, a vision of Pervasive Lifelong User-models that are Scrutable.