![]() |
![]() |
University of Birmingham > Talks@bham > Human Computer Interaction seminars > Location Privacy in Opportunistic Mobile Social Networks
Location Privacy in Opportunistic Mobile Social NetworksAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Dr Chris Bowers. This talk has been canceled/deleted Mobile devices have widely penetrated our lives today. Many of these devices are capable of detecting, storing and sharing users location information at various precisions reaching a few meters. This raises many privacy issues. Opportunistic mobile social networks (OppMSN), a type of Delay-Tolerant Networks, enable heterogeneous devices to communicate using store-carry-forward paradigm without an infrastructure such as 3G networks, and end-to-end communication path between devices. Users sending queries to location-based services (LBSs) over OppMSN reveal their location information. Subsequently, privacy-conscious users turn off their device’s opportunistic interface to ensure their location privacy which lead to network communication failure. In this talk, we will present LPAF , our proposal for enhancing users’ location-privacy over OppMSN using human social relationships and a lightweight Markov model to drive the privacy preserving protocol. LPAF is a fully distributed and collaborative K-anonymity protocol which protects the users location and ensure better privacy while forwarding queries/replies to untrusted LBSs. This talk is part of the Human Computer Interaction seminars series. This talk is included in these lists:This talk is not included in any other list Note that ex-directory lists are not shown. |
Other listsdddd Analysis Reading Seminar Reading Group in Combinatorics and ProbabilityOther talksQuantum simulations using ultra cold ytterbium Hodge Theory: Connecting Algebra and Analysis Sensing and metrology activities at NPL, India TBC The development of an optically pumped magnetometer based MEG system Ultrafast, all-optical, and highly efficient imaging of molecular chirality |