New Technologies for Network Security and Anomaly Detection
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 June 2025 | Viewed by 866
Special Issue Editor
Interests: network security; data driven security; cryptography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The purpose of this Special Issue is to present up-to-date technologies and research that enable us to maintain network security via network intrusion detection. According to the Google Transparency Report, 99% of Internet traffic is encrypted. Data traffic encryption is one of the most promising ways of protecting users’ privacy. However, it makes us face many new challenges in network-based security controls such as intrusion detection/prevention systems. One of the biggest challenges is that the conventional signature-based detection mechanism does not work over encrypted data traffic. Various alternative approaches have been proposed that use advanced cryptographic technologies and Artificial Intelligence and Machine Learning (AI/ML) techniques. The advancement in these techniques enables network-based security controls to detect anomalies from encrypted data using signature-based detection mechanisms or heuristics such as behavior analysis. We also aim to seek solutions to various network settings from heterogeneous IoT networks to cloud computing. The topic of this Special Issue includes advanced techniques that can contribute to network intrusion or anomaly detection in the modern Internet environment. They include, but are not limited to, the following:
- Innovative network security architectures for intrusion detection;
- Intrusion detection on heterogeneous IoT networks;
- Fog/edge/cloud computing security;
- AI/ML techniques for anomaly detection;
- Advanced cryptographic techniques for intrusion detection;
- Malware/ransomware identification and prevention.
Prof. Dr. Jongkil Kim
Guest Editor
Manuscript Submission Information
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Keywords
- network security
- intrusion detection
- fog/edge/cloud computing security
- anomaly detection
- cryptographic techniques
- malware/ransomware identification and prevention
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