Table of Content

AI and Machine Learning for Secure Mobile Cloud Computing and Web based Applications

Submission Deadline: 31 January 2023 Submit to Special Issue

Guest Editors

Prof. Brij B. Gupta, Asia University, Taiwan
Prof. Dragan Peraković, University of Zagreb, Croatia
Prof. Gregorio Martinez Perez, University of Murcia (UMU), Spain

Summary

Cybersecurity is an essential need for a modern society in which information technology and services pervade every aspect of our lives. However, it is challenging to achieve, as technology is changing at a rapid speed and our systems have become ever more complex. We are gradually becoming more dependent upon such information and communication infrastructures, and the threats we face are organized by attackers or cybercriminals to exploit our dependency. Moreover, cyberspace is considered the fifth battlefield after land, air, water, and space. Moreover, mobile devices face many resources and other challenges (battery life, storage, bandwidth, security, etc.). Moreover, the security of Mobile Cloud Computing and Web based Applications is becoming challenging day by day. Therefore, AI and machine learning approaches are more appropriate to secure mobile cloud computing and web-based applications.

 

The objective of this special issue is to investigate the novel AI and machine learning based techniques that lead to secure mobile cloud computing and web-based applications. Contributions may present and solve open technical problems, integrate novel solutions efficiently, and focus on the performance evaluation and comparison with existing standards.

 

Topics to be discussed in this special issue include (but are not limited to) the following:

• Security and privacy issues in Web based applications

• AI and machine learning for mobile cloud computing-based applications

• Security analysis and verification of communication protocol in mobile cloud computing (MCC)

• Privacy-preserving protocols in mobile cloud computing

• Access control mechanisms in mobile cloud computing

• Cryptography cloud storage

• AI and machine learning for web-based applications

• Cloud and IoT Security

• Cyber Physical Systems (CPSs) and Fog Computing

• MCC Pricing and billing models

• Data storage, processing, and management at MCC platform

• Admission control for MCC

• Social engineering, insider threats, advanced spear phishing

• Incident Handling and Penetration Testing

• Forensics of Virtual and MCC Environments

• Security protocols in MCC

• Innovative authentication methods to mobile devices and services

• Mobile application and application store security and privacy;

• Mobile malware collection, statistics, and analysis;

• Bots on mobile devices;

• Reverse engineering and automated analysis of mobile malware;

• MCC Resource scheduling that enhances the reliability and scalability

• MCC Resources monitoring mechanism and utilization measuring mechanism

• MCC resources allocation and management

• MCC virtualization



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