Library and Information Science Commons^™

Cheating Detection In A Privacy Preserving Driving Style Recognition Protocol, Ethan Sprissler

Legacy Theses & Dissertations (2009 - 2024)

The growth of cloud-based services collecting user data for online analytical processing (OLAP), machine learning, and applications relating to the Internet of Things (IoT) has also increased concern with data privacy. Privacy-preserving data sharing using Secure Multiparty Communication (SMC) enables the exchange of encrypted data between parties to perform calculations while maintaining data privacy for both parties simultaneously. This research builds on established work that proposed a privacy-preserving driving style recognition protocol designed to work well with semi-honest actors. In this protocol, both parties follow the established algorithms and do not overtly attempt to deceive the other party into revealing …