The tool will make data sharing convenient and safe, at a time when organisations need to flexibly utilise all available data to participate in a data-driven and automated attack landscape, explains Sowmya Ramasubramanian, Reporting Trainee at The Hindu.
A new tool called 'DoppelGANger' employs machine learning techniques to enable companies to exchange data with one another without revealing confidential information.
Developed by researchers at Carnegie Mellon University and technology company IBM, the tool uses utilises generative adversarial networks (GAN), which employ machine learning techniques to synthesise datasets that have the same statistics as the original data. GAN refers to a system made up of neural network models that compete with each other to capture and analyse data...
The CMU and IBM team says the tool requires no prior knowledge of the dataset and its configurations, as the GANs themselves are able to generalise across different datasets and use cases. This makes the tool highly flexible, the researchers say, and that flexibility is key to data sharing in cybersecurity situations.
Source: The Hindu