Special Issue "Management of Security, Privacy and Trust of Multimedia Data in Mobile devices communication"

Submission Deadline: 30 November 2020
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Guest Editors
Dr. Gregorio Martinez Perez, University of Murcia (UMU), Spain
Dr. B. B. Gupta, National Institute of Technology, Kurukshetra, India
Byung-Gyu Kim, Sookmyung Women's University, Seoul, Rep. of Korea
Yining Liu, Guilin University of Electronic Technology, China


Mobile communication is being developed with an exponential growth of mobile users, how to protect mobile networks against various attacks has become a big challenge. Taking mobile devices as an example, these devices are tiny, and users may lose them easily. Moreover, these devices have become one of the most demanding goods which attract thieves because of their resale value. Moreover, multimedia data during the mobile communication including network, media and devices is an important issue to handle. Moreover, explosion of multimedia data has created unprecedented opportunities and fundamental security challenges as they are not just big in volume, but also unstructured and multi-modal. In the past years, as per the reports of cyber crime, the rise of malware and attacks on mobile communication can be easily said. As a result, there is an increasing need for secure solutions to protect users' private and sensitive multimedia data in the mobile environment. This special issue will focus on mobile context and aims to request original research papers that discuss the management of security, privacy and trust of multimedia data in mobile communication including design, configuration and implementation of networks, media and devices.

• Definition, evaluation, and deployment requirements of 5G/6G systems
• Security, Privacy and Trust of multimedia data in mobile communication
• Trust evaluation on mobile networks/devices
• Detection of malicious information propagation in mobile networks
• Models, methods, and tools for testing the security of mobile networks
• Security, privacy and trust of multimedia big data in mobile networks
• Security of multimedia data in Semantic web based social network
• Security of multimedia data in communication systems
• Security of multimedia data in Information Systems
• Security of multimedia data in MCC
• Management of security and privacy of multimedia data in wireless network
• Massive MIMO technologies
• Millimeter wave wireless communication technologies
• Full-duplex radios for 5G/6G mobile communications
• Massive connectivity and synchronous transmission and random access
• Heterogeneous wireless network architecture design and implementation
• Privacy and Security of Building Data
• Cryptography, authentication, authorisation and usage control for multimedia data in mobile networks
• Security and privacy of multimedia Data in Web service
• Evolutionary algorithms for mining social networks for decision support
• Interference coordination in 5G/6G mobile communications
• Low latency transmission technologies
• Energy harvesting wireless communication technologies
• Energy-efficient technologies in 5G/6G mobile communications
• Distributed caching in 5G/6G mobile communications
• Device-to-device/machine-to-machine communications
• Tactile internet applications
• Cloud-assist wireless transmission
• Big data analytical modeling and solutions for wireless networks
• Mobile Cloud architecture and platform
• Software-defined wireless networks
• Evolution solutions from conventional cellular mobile to content-aware wireless communications
• Joint multimedia processing and wireless transmission design for wireless multimedia communications
• Adversarial modeling Vulnerability
• Assessment and testing Intrusion detection and prevention schemes
• Tracing back mobile attackers
• Impact of human social behavior on mobile usage
• Secure routing and access control
• Mobile authentication mechanisms
• Security testing of new or existing usability features
• Agent based intrusion surveillance
• Wireless Access Technologies
• Multimedia security issues for tackling intruders

Published Papers
  • Towards Improving the Intrusion Detection through ELM (Extreme Learning Machine)
  • Abstract An IDS (intrusion detection system) provides a foremost front line mechanism to guard networks, systems, data, and information. That’s why intrusion detection has grown as an active study area and provides significant contribution to cyber-security techniques. Multiple techniques have been in use but major concern in their implementation is variation in their detection performance. The performance of IDS lies in the accurate detection of attacks, and this accuracy can be raised by improving the recognition rate and significant reduction in the false alarms rate. To overcome this problem many researchers have used different machine learning techniques. These techniques have limitations… More
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