Editing Quantum machine learning (section)

==Using quantum networks for data protection==
The second issue that needs to be considered is the security of data. While startups may be developing quantum machine learning algorithms today, and get cloud access to quantum computers, getting access to sensitive data may not be possible today or in the future.

A solution to this problem for classical machine learning is to add noise to the data to preserve privacy. Machine learning algorithms are naturally resistant to noise (an algorithm that recognizes a cat on a picture should be able to recognize a cat on a noisy picture). Quantum networks being inherently noisy and lossy, we might be able to take advantage of that feature to enhance security and privacy.