Category: .Net

Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks

Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks   Abstract: Releasing social network data could seriously breach user privacy. User profile and friendship relations are inherently private. Unfortunately, it is possible to predict sensitive information carried in released data latently by utilizing data mining techniques. Therefore, sanitizing network data prior to release is […]


Service Rating Prediction by Exploring Social Mobile User’s Geographical Locations

Service Rating Prediction by Exploring Social Mobile User’s Geographical Locations (IEEE 2017 – 2018) Abstract: Recently, advances in intelligent mobile device and positioning techniques have fundamentally enhanced social networks, which allows users to share their experiences, reviews, ratings, photos, check-ins, etc. The geographical information located by smart phone bridges the gap between physical and digital […]