A Four-Dimensional Space-Based Data Multi-Embedding Mechanism for Network Services
Mianjie Li, Haozheng Cui, Chihui Liu, Chun Shan, Xiaojiang Du, Mohsen Guizani
Abstract
In the age of data science and connected devices of all kinds, users have gained a lot of convenience. However, the massive data generated by users from the communication network is faced with security problems such as intrusion, tampering, hijacking, etc. According to the properties of covert transmission, the network with data covert embedding becomes an effective means to solve these challenges. In this paper, we propose a four-dimensional space-based data multi-embedding mechanism to protect data in the network. Specifically, a feature extractor is first used to extract vectors for embedding. Next, a Schmitt-based four-dimensional space is constructed, two of which are used to embed robust data to hide confidential information. The other two dimensions are used to embed fragile data to detect whether the signal has been tampered with. According to the experimental comparison with other methods, it shows that the method proposed in this paper achieves satisfactory performance.