Research on Security and Privacy Problem in the Data Life Cycle for the IoT Scenario

Sensors have been deployed into different scenarios to collect data, including health data, environmental data, etc. Data have been collected, transmitted, analyzed, etc. Those data are highly related to people's privacy, protecting data privacy becomes necessary. Different methods have been applied to protect data privacy during the life cycle in the Internet of Things scenarios. At the data collecting phase, data aggregation methods are proposed. At the data transmission phase, mutual authentication and key establishment schemes are proposed to help entities to build a secure two-way communication channel, data can be transmitted securely. At the data analyzing phase, privacy-preserving machine learning methods have been discussed, including collaboratively learning and other encrypted machine learning as a service technology, they can protect users' data privacy at the training phase and inference phase respectively. In this study, we mainly discussed these kinds of methods for protecting data security and privacy in the Internet of Things scenario.