Security and Communication Networks

Machine Learning for Wireless Multimedia Data Security 2020


Publishing date
01 Nov 2020
Status
Closed
Submission deadline
03 Jul 2020

Lead Editor

1Nanjing University of Information Science and Technology, Nanjing, China

2Texas Tech University, Texas, USA

3Technical University of Denmark (DTU), Kongens Lyngby, Denmark

4Nanjing Institute of Technology, Nanjing, China

This issue is now closed for submissions.

Machine Learning for Wireless Multimedia Data Security 2020

This issue is now closed for submissions.

Description

With the rapid development of multimedia technologies, the collection and modification of wireless multimedia data have become greatly convenient and easy. Meanwhile, the wireless multimedia data also made sensitive information available to potential attackers. The credibility of digital wireless multimedia data has thus decreased if the wireless multimedia data cannot be well protected. In addition, the copyright and privacy of wireless multimedia data also are easy to be infringed. Especially, the data storage and computation have to be delegated to the powerful but always untrusted cloud, which has led to a series of challenging security and privacy threats.

Nowadays, artificial intelligence (AI) technology has been widely used in academia and industry. Machine learning can be regarded as one of the most important AI technologies, and it has been successfully used in image processing, pattern recognition, computer vision, natural language processing, and so on. Currently, the traditional steganography and security of encrypted wireless multimedia data face a lot of challenges, thus, new types of steganography and encryption of wireless multimedia data, including audio, image, and video, are urgently needed to explore. Moreover, in a new environment like cloud computing, the distribution and processing of wireless multimedia data also face more new challenges. For example, how to securely process wireless multimedia data in cloud computing to preserve the privacy of wireless multimedia data, and how to reliably solve a multiparty computation by outsourcing are still open questions, and so on.

The aim of this Special Issue is to collate original research and review articles with a focus on issues that arise from using machine learning for wireless multimedia data security.

Potential topics include but are not limited to the following:

  • Machine learning for wireless multimedia data security
  • Machine learning for wireless multimedia data transmission security
  • Machine learning for reversible data hiding in plaintext or ciphertext multimedia
  • Machine learning for reliable computing and outsourcing of wireless multimedia data
  • Machine learning for threat detection in wireless multimedia data system
  • Machine learning for privacy protection of wireless multimedia data
  • Machine learning for wireless multimedia information hiding and fingerprinting
  • Machine learning for wireless multimedia authentication and encryption
  • Machine learning for wireless multimedia data copyright protection
  • Machine learning for wireless multimedia data watermarking

Articles

  • Special Issue
  • - Volume 2020
  • - Article ID 8845942
  • - Research Article

Community Detection Based on DeepWalk Model in Large-Scale Networks

Yunfang Chen | Li Wang | ... | Wei Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 8887596
  • - Research Article

A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes

Yonghua Gong | Lei Chen | Tinghuai Ma
  • Special Issue
  • - Volume 2020
  • - Article ID 8822126
  • - Research Article

Accurate Computation of Fractional-Order Exponential Moments

Shujiang Xu | Qixian Hao | ... | Jian Li
  • Special Issue
  • - Volume 2020
  • - Article ID 5874935
  • - Research Article

Preserving Privacy in Multimedia Social Networks Using Machine Learning Anomaly Detection

Randa Aljably | Yuan Tian | Mznah Al-Rodhaan
  • Special Issue
  • - Volume 2020
  • - Article ID 8863169
  • - Research Article

An Encrypted Traffic Identification Scheme Based on the Multilevel Structure and Variational Automatic Encoder

Jiangtao Zhai | Huaifeng Shi | ... | Junjun Xing
  • Special Issue
  • - Volume 2020
  • - Article ID 8848315
  • - Research Article

A Multimode Network Steganography for Covert Wireless Communication Based on BitTorrent

Mingqian Wang | Weijie Gu | Changshen Ma
  • Special Issue
  • - Volume 2020
  • - Article ID 8846230
  • - Research Article

VoNR-IPD: A Novel Timing-Based Network Steganography for Industrial Internet

Mingqian Wang | Shuai Cao | Yunliang Wang
Security and Communication Networks
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Acceptance rate10%
Submission to final decision143 days
Acceptance to publication35 days
CiteScore2.600
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