July 5, 2022, 1:20 a.m. | Hojjat Navidan, Vahideh Moghtadaiee, Niki Nazaran, Mina Alishahi

cs.CR updates on arXiv.org arxiv.org

The advent of numerous indoor location-based services (LBSs) and the
widespread use of many types of mobile devices in indoor environments have
resulted in generating a massive amount of people's location data. While
geo-spatial data contains sensitive information about personal activities,
collecting it in its raw form may lead to the leak of personal information
relating to the people, violating their privacy. This paper proposes a novel
privacy-aware framework for aggregating the indoor location data employing the
Local Differential Privacy …

differential privacy hide local location location privacy privacy

SOC 2 Manager, Audit and Certification

@ Deloitte | US and CA Multiple Locations

Digital Trust Cyber Transformation Senior

@ KPMG India | Mumbai, Maharashtra, India

Security Consultant, Assessment Services - SOC 2 | Remote US

@ Coalfire | United States

Sr. Systems Security Engineer

@ Effectual | Washington, DC

Cyber Network Engineer

@ SonicWall | Woodbridge, Virginia, United States

Security Architect

@ Nokia | Belgium