Guest Editor(s)
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- Assoc. Prof. Weizhi Meng
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
Website | E-mail
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- Assoc. Prof. Qi Li
- Institute for Network Sciences and Cyberspace, Beijing National Research Centre for Information Science and Technology (BNRist), Tsinghua University, Beijing, China.
Website | E-mail
Special Issue Introduction
As smart techniques and the Internet of Things (IoT) are improving by leaps and bounds, a smart world is becoming feasible, such as smart cities and smart homes. For example, a smart city will collect various data, supply information, and process/manage traffic and transportation with information and communication technology (ICT). However, malicious applications (malware) are still a significant threat to such smart environment, i.e., ransomware attacks are expected to increase and newer forms to become more sophisticated and disruptive. The damages from malware cybercrime, especially ransomware, are assumed to hit $6 trillion in 2021 (up from $3 trillion in 2015). Hence there is a significant need to research and analyse the current evolution of malware and propose suitable solutions to protect our assets against malware.
This special issue intends to gather cutting-edge results on malware analysis and detection in the smart world. The aim is to promote malware research, including but not limited to design methods, crypto and post-quantum, automation techniques, and intrusion detection and prevention.
In particular, the topic of interest includes but is not limited to:
- Malware and unwanted software
- Program analysis and reverse engineering
- Machine learning for malware detection
- Intrusion detection and prevention
- Lineage analysis of malware family
- Botnets and ransomware
- Various types of IoT malware and their defense mechanisms
- New types of malware and their defenses
- Mobile and smartphone security
- Vulnerability analysis techniques
- Denial-of-Service attacks and defenses
- Security measurement studies
- Digital forensics
Submission Deadline
31 May 2022