Research on Technology Against Deepfake
Xia Wei, Wenjun Zhang, Guozhu Bai, Bo Li · 2023
With the help of social networks, Deepfakes enable false information to be presented to netizens in a highly credible manner, which will have a huge impact on individuals, organizations, and countries. It will also pose huge information security risks to individuals, organizations, and countries. Some countries are even seeking to weaponize “deep counterfeiting technology”, which poses significant security risks and has become a focus and difficulty of research both domestically and internationally. Scholars both domestically and internationally are exploring different deep forgery detection countermeasures to eliminate negative impacts. It was found that at the technical level, it can be divided into two types based on processing methods: passive detection algorithms and active defense technologies. According to the different processing objects, passive detection algorithms can be divided into two categories: deep forged image detection and deep forged video detection. In terms of active defense technology, content traceability technology is mainly used to build a trusted system for digital content in the internet to ensure the source security of content. This paper summarizes the current research situation of combating deepfake technology based on blockchain technology from three aspects of building a trusted network, tracing deepfake and content Tamper resistance prevention, analyzes the limitations and risks of using blockchain technology against deepfake technology, and discusses the future research direction.