Adaptive blurring of sensor data to balance privacy and utility for ubiquitous services

Given the trend towards mobile computing, the next generation of ubiquitous “smart” services will have to continuously analyze surrounding sensor data. More than ever, such services will rely on data potentially related to personal activities to perform their tasks, e.g. to predict urban traffic or local weather conditions. However, revealing personal data inevitably entails privacy risks, especially when data is shared with high precision and frequency. For example, by analyzing the precise electric consumption data, it can be inferred if a person is currently at home, however this can empower new services such as a smart heating system. Access control (forbid or grant access) or anonymization techniques are not able to deal with such trade-off because whether they completely prohibit access to data or lose source traceability. Blurring techniques, by tuning data quality, offer a wide range of trade-offs between privacy and utility for services. However, the amount of ubiquito...

• Type: Journal
• Year: 2015
• Where: SAC
• Authors: Assaad Moawad, Thomas Hartmann 0001, François Fouquet, Jacques Klein, Yves Le Traon
• Keywords: Applied Computing, SAC 2015