Name
Title | ||
|---|---|---|
Anti-Forensics of Environmental-Signature-Based Audio Splicing Detection and Its Countermeasure via Rich-Features Classification. |
Abstract | ||
|---|---|---|
Numerous methods for detecting audio splicing have been proposed. Environmental-signature-based methods are considered to be the most effective forgery detection methods. The performance of existing audio forensic analysis methods is generally measured in the absence of any anti-forensic attack. Effectiveness of these methods in the presence of anti-forensic attacks is therefore unknown. In this p... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIFS.2016.2543205 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
Splicing,Forensics,Speech,Acoustics,Authentication,Robustness,Feature extraction | Spectral properties,Authentication,Pattern recognition,Computer science,Robustness (computer science),Feature extraction,Speech recognition,Exploit,Synthetic data,Forgery detection,RNA splicing,Artificial intelligence | Journal |
Volume | Issue | ISSN |
11 | 7 | 1556-6013 |
Citations | PageRank | References |
1 | 0.38 | 26 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Zhao | 1 | 105 | 16.53 |
| Yifan Chen | 2 | 474 | 70.39 |
| Rui Wang | 3 | 168 | 21.18 |
| Hafiz Malik | 4 | 183 | 23.47 |