The goal is to establish a secure and fair circulation platform for big data, enabling big data collection, analysis, utilization and feedback to data owner. Our research mainly focus on 4 specific fields as follows:
1.Secure Data Management
To design and implement highly reliable secure data secure management system. Within the system, data management server is able to perform dynamic data processing such data adding, data updating and deleting, furthermore, capable of executing the data recovering while keeping cost lower for data owner.
This research topic considers the bidirectional cyber-attacks, both internal and external. We undertake to construct a client-oriented framework for detecting the SSL/TLS attack at a early stage in a simple way. We undertake to build a robust system to enhance the security against malicious server and external server attack with consideration of crystallographic primitives in use, while providing the functionality for hiding memory access pattern.
3.Secure Data Mining
It aim to build a flexible and extendable privacy-preserving data mining framework according to required privacy setting of data owner in a secured way, data user can perform privacy-preserving computation for their target functionality within the framework.
4.Secure Data Utility
Toward developing the core technologies for secure and fair P4V of big data analysis result, feedback and utilization, we make effort to implement the anonymous traceability for data owner from data analysis results and provide correctness proof and verification of trace without violating the anonymity.