FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network

• URL: http://arxiv.org/abs/2011.11278v2
• Date: Thu, 10 Dec 2020 04:10:21 GMT
• Title: FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network
• Authors: He Zhu and Dianbo Liu
• Abstract summary: disinformation strategy can be adapted into data science to protect valuable private and sensitive data. Huge amount of private data are being generated from personal devices such as smart phone and wearable. Building a secure data transfer and storage infrastructure to preserving privacy is costly in most cases and there is always a concern of data security due to human errors. We propose a method, named FakeSafe, to provide human level data protection using generative adversarial network with cycle consistency.
• Score: 4.987581730476023
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The concept of disinformation is to use fake messages to confuse people in order to protect the real information. This strategy can be adapted into data science to protect valuable private and sensitive data. Huge amount of private data are being generated from personal devices such as smart phone and wearable in recent years. Being able to utilize these personal data will bring big opportunities to design personalized products, conduct precision healthcare and many other tasks that were impossible in the past. However, due to privacy, safety and regulation reasons, it is often difficult to transfer or store data in its original form while keeping them safe. Building a secure data transfer and storage infrastructure to preserving privacy is costly in most cases and there is always a concern of data security due to human errors. In this study, we propose a method, named FakeSafe, to provide human level data protection using generative adversarial network with cycle consistency and conducted experiments using both benchmark and real world data sets to illustrate potential applications of FakeSafe.

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