Discovery Projects - Grant ID: DP150104871 [ 2015 - 2017 ]

Research Grant

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Researchers Prof Hong Shen

Brief description Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving this problem. It develops a set of effective methods for privacy-preserving data publication through combining randomization with anonymization, and for classifying the published data through uncertainty leveraging by probabilistic reasoning and accuracy lifting by inter-flow correlation analysis and active learning.

Funding Amount 340300

Funding Scheme Discovery Projects

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