Generative Steganography Based on Long Readable Text Generation-Reference-Cited by-同舟云学术

Generative Steganography Based on Long Readable Text Generation

Published:2022 Issue: Volume: Page:1-11
ISSN:2329-924X
Container-title:IEEE Transactions on Computational Social Systems
language:
Short-container-title:IEEE Trans. Comput. Soc. Syst.

Author:

Cao Yi¹^ORCID,Zhou Zhili²^ORCID,Chakraborty Chinmay³^ORCID,Wang Meimin¹^ORCID,Wu Q. M. Jonathan⁴^ORCID,Sun Xingming¹,Yu Keping⁵^ORCID

Affiliation:

1. Engineering Research Center of Digital Forensics, Ministry of Education, School of Com- puter and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China.

2. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangdong 510006, China

3. Department of Electronics and Communication Engineering, Birla Institute of Technology at Mesra, Ranchi 835215, India

4. Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.

5. Graduate School of Science and Engineering, Hosei University, Tokyo 184-8584, Japan.

Funder

National Natural Science Foundation of China

Japan Society for the Promotion of Science JSPS through Grants-in-Aid for Scientific Research KAKENHI

Jiangsu Basic Research Programs-Natural Science Foundation

Priority Academic Program Development of Jiangsu Higher Education Institutions PAPD Fund

Collaborative Innovation Center of Atmospheric Environment and Equipment Technology CICAEET Fund China

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/6570650/6780646/09778236.pdf?arnumber=9778236

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