Name
Title | ||
|---|---|---|
ANiTW: A Novel Intelligent Text Watermarking Technique for Forensic Identification of Spurious Information on Social Media |
Abstract | ||
|---|---|---|
•In this research, we propose a novel intelligent text watermarking technique called ANiTWwhich employs an instancebased learning algorithm to hide an invisible watermark into Latin text-based information.•The ANiTWcan extract the integrity rate and provide proof of ownership for sensitive text-based information on social media, even if a malicious user manipulates a portion of the watermarked information.•The proposed technique provides superior efficiency compared to the existing approaches concerning evaluation criteria. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.cose.2019.101702 | Computers & Security |
Keywords | Field | DocType |
Watermarking,Steganography,Reliability,Text Integrity,Text Mining | Steganography,Digital watermarking,Social media,Computer science,Computer security,Watermark,Plain text,Information sensitivity,Digital media,The Internet | Journal |
Volume | ISSN | Citations |
90 | 0167-4048 | 3 |
PageRank | References | Authors |
0.40 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Milad Taleby Ahvanooey | 1 | 9 | 3.90 |
| Li Qian-Mu | 2 | 33 | 14.78 |
| Xuefang Zhu | 3 | 3 | 0.40 |
| Mamoun Alazab | 4 | 347 | 52.15 |
| Jing Zhang | 5 | 22 | 5.41 |