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Full-Text Articles in Physical Sciences and Mathematics
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Research Collection School Of Computing and Information Systems
Crowdsourcing platforms such as Amazon Mechanical Turk and Google Consumer Surveys can profile users based on their inputs to online surveys. In this work we first demonstrate how easily user privacy can be compromised by collating information from multiple surveys. We then propose, develop, and evaluate a crowdsourcing survey platform called Loki that allows users to control their privacy loss via atsource obfuscation.
A Highly Efficient Rfid Distance Bounding Protocol Without Real-Time Prf Evaluation, Yunhui Zhuang, Anjia Yang, Duncan S. Wong, Guomin Yang, Qi Xie
A Highly Efficient Rfid Distance Bounding Protocol Without Real-Time Prf Evaluation, Yunhui Zhuang, Anjia Yang, Duncan S. Wong, Guomin Yang, Qi Xie
Research Collection School Of Computing and Information Systems
There is a common situation among current distance bounding protocols in the literature: they set the fast bit exchange phase after a slow phase in which the nonces for both the reader and a tag are exchanged. The output computed in the slow phase is acting as the responses in the subsequent fast phase. Due to the calculation constrained RFID environment of being lightweight and efficient, it is the important objective of building the protocol which can have fewer number of message flows and less number of cryptographic operations in real time performed by the tag. In this paper, we …
Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing, Fengjun Li, Bo Luo, Peng Liu, Dongwon Lee, Chao-Hsien Chu
Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing, Fengjun Li, Bo Luo, Peng Liu, Dongwon Lee, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Today’s organizations raise an increasing need for information sharing via on-demand access. Information brokering systems (IBSs) have been proposed to connect large-scale loosely federated data sources via a brokering overlay, in which the brokers make routing decisions to direct client queries to the requested data servers. Many existing IBSs assume that brokers are trusted and thus only adopt server-side access control for data confidentiality. However, privacy of data location and data consumer can still be inferred from metadata (such as query and access control rules) exchanged within the IBS, but little attention has been put on its protection. In this …
Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao
Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao
Research Collection School Of Computing and Information Systems
Most social networking platforms protect user's private information by limiting access to it to a small group of members, typically friends of the user, while allowing (virtually) everyone's access to the user's public data. In this paper, we exploit public data available on Facebook to infer users' undisclosed interests on their profile pages. In particular, we infer their undisclosed interests from the public data fetched using Graph APIs provided by Facebook. We demonstrate that simply liking a Facebook page does not corroborate that the user is interested in the page. Instead, we perform sentiment-oriented mining on various attributes of a …
Verifiable And Private Top-K Monitoring, Xuhua Ding, Hwee Hwa Pang
Verifiable And Private Top-K Monitoring, Xuhua Ding, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
In a data streaming model, records or documents are pushed from a data owner, via untrusted third-party servers, to a large number of users with matching interests. The match in interest is calculated from the correlation between each pair of document and user query. For scalability and availability reasons, this calculation is delegated to the servers, which gives rise to the need to protect the privacy of the documents and user queries. In addition, the users need to guard against the eventuality of a server distorting the correlation score of the documents to manipulate which documents are highlighted to certain …