Special Issue "Applied Cryptography, Network Security, and Privacy Protection"
A special issue of Cryptography (ISSN 2410-387X).
Deadline for manuscript submissions: closed (20 November 2022) | Viewed by 5064
Interests: data security and privacy protection; security scheme and protocol design; network and application security
Cryptography has long been widely used to solve various security and privacy problems in the Internet. In recent years, along with the rise and rapid development of mobile networks, sensor networks, and new networks like IoT and blockchain networks, new security and privacy issues are emerging. New network applications pose new challenges, forcing the development of cryptographic methods and tools with higher efficiency and stronger security. On the other hand, the emergence and application of these networks have also greatly enriched and strengthened the infrastructure of the information world, opening up new possibilities for solving various security and privacy problems and developing new cryptographic tools and methods. We aim to use this Special Issue to attract academic and industrial colleagues to share their latest discoveries, ideas, and breakthroughs in the fields of applied cryptography, network security, and privacy protection. The main topics include, but are not limited to, the following:
- Novel cryptographic tools/protocols for network security and privacy protection;
- Secure multiparty party computations;
- Mobile network security/privacy;
- Sensor network security/privacy;
- Blockchain network security/privacy;
- Blockchain-based security/privacy protection;
- Security and privacy protection for big data and IoT;
- Privacy-preserving federated learning for AIoT;
- Privacy protection measurement metrics;
- Privacy-preserving protocols for outsourcing computation;
- Secure machine learning techniques for network security;
- Secure data integrity and validation techniques;
- Security/privacy/trust issues in network architectures;
- Privacy-preserving pervasive computing techniques;
- Adaptive data privacy and security solutions for edge computing;
- Big data analytics and privacy-preserving techniques;
- Machine-learning-based intrusion detection.
Prof. Dr. Hui Zhu
Dr. Yuan Zhang
Manuscript Submission Information
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