Traffic data over networks may leak personal information, such as location information and products purchased at online stores. Even if the traffic data are encrypted, attackers can obtain personal information from various side-channel information. In addition, because the users of the Internet are anonymized, the information sent by anonymized Internet users cannot be trusted. Recently, false information, so-called fake news on social networking services, and impersonation of other people utilizing fake video images, known as deep fakes, have also become problems. In the Big data era, if the data are not trustworthy, the results of that analysis are also unreliable. In this way, the reliability of the data flowing through the network should be ensured. In this research area, we are studying technologies to prevent privacy leaks from data flowing over the network and to ensure the trustworthiness of the data themselves.
Analysis of Trustworthiness in Data Trading and Its Technical Issues, 2022 Symposium on Cryptography and Information Security(SCIS2022)
