Label-Only Membership Inference Attack against \\Node-Level Graph Neural Networks

Graph Neural Networks (GNNs), inspired by Convolutional Neural Networks (CNNs), aggregate the message of nodes' neighbors and structure information to acquire expressive representations of nodes for node classification, graph classification, and link prediction. Previous studies have indicated that node-level GNNs are vulnerable to Membership...

Graph Encryption for Shortest Path Queries with k Unsorted Nodes

Shortest distance queries over large-scale graphs bring great benefits to various applications, i.e., save planning time and travelling expenses. To protect the sensitive nodes and edges in the graph, a user outsources an encrypted graph to an untrusted server without losing the query ability. However, no prior work has considered the user...

Repetitive, Oblivious, and Unlinkable SkNN Over Encrypted-and-Updated Data on Cloud

Location-Based Services (LBSs) depend on a Service Provider (SP) to store data owners’ geospatial data and to process data users’ queries. For example, a Yelp user queries the SP to retrieve the k nearest Starbucks by submitting her/his current location. It is well-acknowledged that location privacy is vital to users and several prominent...

Where to Meet a Driver Privately: Recommending Pick-Up Locations for Ride-Hailing Services

Ride-Hailing Service (RHS) has motivated the rise of innovative transportation services. It enables riders to hail a cab or private vehicle at the roadside by sending a ride request to the Ride-Hailing Service Provider (RHSP). Such a request collects rider’s real-time locations, which incur serious privacy concerns for riders. While there are...