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Full-Text Articles in Physical Sciences and Mathematics
Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth
Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth
Kno.e.sis Publications
Modern healthcare systems now rely on advanced computing methods and technologies, such as IoT devices and clouds, to collect and analyze personal health data at unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of privacy nightmare. In this paper, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth - a personalized digital healthcare information system …
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen
Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen
Kno.e.sis Publications
This paper presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.
Sempush: Privacy-Aware And Scalable Broadcasting For Semantic Microblogging, Pavan Kapanipathi, Julia Anaya, Alexandre Passant
Sempush: Privacy-Aware And Scalable Broadcasting For Semantic Microblogging, Pavan Kapanipathi, Julia Anaya, Alexandre Passant
Kno.e.sis Publications
Users of traditional microblogging platforms such as Twitter face drawbacks in terms of (1) Privacy of status updates as a followee - reaching undesired people (2) Information overload as a follower - receiving uninteresting microposts from followees. In this paper we demonstrate distributed and user-controlled dissemination of microposts using SMOB (semantic microblogging framework) and Semantic Hub (privacy-aware implementation of PuSH3 protocol) . The approach leverages users' Social Graph to dynamically create group of followers who are eligible to receive micropost. The restrictions to create the groups are provided by the followee based on the hastags in the micropost. Both SMOB …
Privacy-By-Design In Federated Social Web Applications, Alexandre Passant, Owen Sacco, Julia Anaya, Pavan Kapanipathi
Privacy-By-Design In Federated Social Web Applications, Alexandre Passant, Owen Sacco, Julia Anaya, Pavan Kapanipathi
Kno.e.sis Publications
No abstract provided.
Privacy-Aware An Scalable Content Dissemination In Distributed Social Networks, Pavan Kapanipathi, Julia Anaya, Amit P. Sheth, Brett Slatkin, Alexandre Passant
Privacy-Aware An Scalable Content Dissemination In Distributed Social Networks, Pavan Kapanipathi, Julia Anaya, Amit P. Sheth, Brett Slatkin, Alexandre Passant
Kno.e.sis Publications
Centralized social networking websites raise scalability issues - due to the growing number of participants - and, as well as, policy concerns - such as control, privacy and ownership over the user's published data. Distributed Social Networks aim to solve this issue by enabling architecture where people own their data and share it their own way. However, the privacy and scalability challenge is still to be tackled. This paper presents a privacy-aware extension to Google's PubSubHubbub protocol, using Semantic Web technologies, solving both the scalability and the privacy issues in Distributed Social Networks. We enhanced the traditional feature of PubSubHubbub …