TY - JOUR
T1 - A Four-Dimensional Space-Based Data Multi-Embedding Mechanism for Network Services
AU - Li, Mianjie
AU - Cui, Haozheng
AU - Liu, Chihui
AU - Shan, Chun
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
IEEE
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Communication networks
KW - Data Embedding Mechanism
KW - Data Security
KW - Detectors
KW - Feature extraction
KW - Four-Dimensional Space
KW - Frequency-domain analysis
KW - Intrusion
KW - Monitoring
KW - Security
KW - Time-domain analysis
UR - http://www.scopus.com/inward/record.url?scp=85179835804&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85179835804&partnerID=8YFLogxK
U2 - 10.1109/TNSM.2023.3339674
DO - 10.1109/TNSM.2023.3339674
M3 - Article
AN - SCOPUS:85179835804
SP - 1
JO - IEEE Transactions on Network and Service Management
JF - IEEE Transactions on Network and Service Management
ER -