Demo Data from EDBT 2026 / reviewers in the wild / expert
Chi Ji
dblp:372/9012
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
0009-0007-8580-0240ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Digital forensics and information hiding · 87% Privacy and data protection · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Digital forensics and information hiding › steganography
reversible data hiding |
0.8 | 1 | 2024 | Reversible Data Hiding in Encrypted Images With Adaptive Huffman Code Based on Dynamic Prediction Axes · IEEE Trans. Multim. 2024 |
Digital forensics and information hiding › steganography › reversible data hiding
reversible data hiding in encrypted images |
0.8 | 1 | 2024 | Reversible Data Hiding in Encrypted Images With Adaptive Huffman Code Based on Dynamic Prediction Axes · IEEE Trans. Multim. 2024 |
Privacy and data protection › privacy-preserving computation › encrypted data processing
encrypted image processing |
0.2 | 1 | 2024 | Reversible Data Hiding in Encrypted Images With Adaptive Huffman Code Based on Dynamic Prediction Axes · IEEE Trans. Multim. 2024 |
Methods — techniques the papers use, named apart from their topics
stream cipher · 0.8multidirectional median edge detector · 0.8dynamic prediction axes · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Reversible Data Hiding in Encrypted Images With Adaptive Huffman Code Based on Dynamic Prediction AxesabstractWith the development of data security and privacy requirements in the field of cloud computing, Reversible Data Hiding in Encrypted Images (RDHEI) in encryption domain has received increasing attention. In order to take full advantage of the spatial and textural features of the original image, reversible data hiding in encrypted image with adaptive Huffman code based on Dynamic Prediction Axes (RDHEI-HDA) is proposed. First, the prediction errors of the original plaintext image are calculated according to the multidirectional median edge detector (M-MED) combined with the Dynamic Prediction Axes which are generated by the spatial correlation of the original image. After encryption process with the stream cipher, the adaptive Huffman coding labeling rule is created for pixel labeling and classification according to the Dynamic Prediction Axes and the distribution of prediction errors. Finally, bit substitution is employed to insert secret data and side information into the image. In Comparison to most of the state-of-the-art RDHEI methods, the experimental results show that the RDHEI-HDA method provides a higher pure payload while ensuring safety. Chi Ji, Guangyong Gao, Yun Q. Shi 0001 |
IEEE Trans. Multim. | 1 |