Guorui Feng, Shanghai University, China, [email protected] (lead guest editor)
Sheng Li, Fudan University, China, [email protected]
Haoliang Li, Nanyang Technological University, Singapore, [email protected]
Shujun Li, University of Kent, UK, [email protected]
Nowadays, more and more mobile devices are being used in our daily life. A vast amount of multimedia data, including audios, images and videos, are produced by the mobile devices every single second. These data are usually stored in a networked environment for people to view, share, or comment. As such, people’s locations, status, or live actions can be seen, tracted or monitored. The shared multimedia data are also under the risk of being illegually used or manupulated. The research of multimedia security is to prevent or detect the criminal activities related to multimedia data, including multimedia authentication, multimedia content security, multimedia privacy security and etc. These fields can be detailed as privacy protection, information hiding and detection, digital forensics, secure processing and etc. To process the huge amount of multimedia data, one important issue is to reduce the burden of the servers effectively. On possible solution is to take advantage of the computational power of the mobile devices. However, the computatinal power of the mobile devices is are usually limited, it is necessary to develop relevant algorithms that are with low computational complexity. In the past few years, researchers have developed a great number of schemes for multimedia security. However, relatively few techniques are applicable on the mobile devices.
This special issue aims at promoting the research on low complexity methods for multimedia security, which includes lightwight learning and modeling for mutimedia data forensics and anti-forensics, low complexity mutimedia privacy protection schemes, low complexity data hiding schemes, and the attacks and counter measures for the authenticy of multimedia data. Related researchers and engineers can contribute with original research that present their work. All submitted papers will be peer-reviewed and selected on the basis of both their quality and relevance to the theme of this special issue. Topics of interest for this special issue include, but are not limited to:
- Statistical learning method for multimedia forensics with low complexity
- Deep learning method for multimedia tampering and forensics with low complexity
- Transfer learning for multimedia secruity with low complexity
- Optimization of multimedia privacy protection and enhancement
- Approximated and incremental computing for watermarking
- Biometrics information protection with low complexityBiometrics spoofing detection with low complexity
- Social multimedia information hiding and detection with low complexity
- Social multimedia secure processing with low complexity
- Applications of low complexity methods for multimedia security related topics
- Survey paper of the above field
Timeline for the Special Issue
Manuscript submission deadline: June 15, 2020
First reviews completed deadline: August 15, 2020
Revised manuscripts deadline: October 15, 2020
Final acceptance deadline: December 15, 2020
Papers submitted to this special issue for possible publication must be original and must not be under consideration for publication in any other journal or conference. If the submission is an extended version of a previously published workshop or conference paper, this should also be explicitly mentioned in the cover letter, as well as the published paper must be cited in the submitted journal version.
The manuscripts will be peer-reviewed strictly following the reviewing procedures. The submissions should clearly demonstrate the evidence of benefits to society or large communities. Originality and impact on society, method novelty will be the major evaluation criteria. Good survey papers on recommendation related topics are strongly encouraged.
The papers must be written in English and must not exceed 30 pages (single column, double space, 12 pt font, including figures, tables, and references). Authors must follow the formatting and submission instructions of MMSJ at https://www.springer.com/530