Principal Investigator: Ng Wee Keong (Associate Professor, School of Computer Science and Engineering (SCSE), NTU)
Team: Ong Jenn Bing (Ph.D student, SCSE NTU)
Mentor: Surendran Vangadasalam (GM Sales, Cisco)


Efficient and secure big data sharing on clouds with fine-grained data access control

Big Data is essential to develop cutting-edge artificial intelligence systems. However, sensitive information can be extracted from big data and therefore may incur privacy issues. We propose a big data shredder that systematically decomposes structured and unstructured data into fragments with partial information. These fragments are non-unique, un-linkable, and not interpretable;  they are distributed among multiple devices or clouds with metadata privacy.

The increasingly complex digital environments nowadays require simple big data security solutions with distributed trust. Our solution is memory-, bandwidth-, and computationally-efficient; most importantly it is keyless, therefore it overcomes the expensive and complicated key management and distribution problems inherent in current data encryption systems. As a mathematical technique, our solution can be easily combined with existing privacy-preserving technologies to provide layered protection; it can also be easily integrated into existing computing platforms, environments, and processes.