The Intrusion Detection and Intrusion Prevention Systems

Dear Colleagues,

Are you ready to dive into the cutting-edge world of cybersecurity? Join us in exploring the dynamic realm of Intrusion Detection and Intrusion Prevention Systems (IDIPS), where every click, every line of code, and every network packet matters.

In today’s digital landscape, where data breaches and cyber threats loom large, the significance of IDIPS cannot be overstated. These systems serve as the first line of defense, tirelessly monitoring, analyzing, and thwarting potential intrusions to safeguard sensitive information and preserve digital integrity. We are pleased to invite you to embark on this journey of discovery and innovation. This Special Issue is not merely another publication opportunity; it is a call to arms for researchers, practitioners, and enthusiasts alike to converge and push the boundaries of knowledge in this critical field.

This Special Issue represents a vast canvas, where the possibilities are endless. We welcome original research articles and reviews spanning a spectrum of themes and methodologies. In this collaborative endeavor, your expertise and insights are invaluable. We look forward to receiving your contributions!

Prof. Dr. Srinivas (Srini) Sampalli
Dr. Marzia Zaman
Dr. Darshana Upadhyay
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied System Innovation is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• innovative intrusion detection techniques
• next-generation intrusion prevention systems
• threat intelligence and behavioral analysis
• scalability and performance optimization
• network traffic analysis and forensics
• zero-day threat detection and response
• intrusion detection system in SCADA-based ICSs
• intrusion prevention system in SCADA-based ICSs
• cross-layer defense mechanisms
• human-centric security and usability
• privacy-preserving intrusion detection
• interoperability and standardization
• anomaly-based detection algorithms
• signature-based detection methods
• host-based intrusion detection systems (HIDS)
• network-based intrusion detection systems (NIDS)
• protocol-based intrusion detection systems
• machine learning in intrusion detection
• adaptive and self-learning IPS solutions
• application layer intrusion detection and prevention
• content-based intrusion detection techniques
• intrusion detection system integration with SIEM (security information and event management)
• evasion techniques and countermeasures for IDS/IPS
• hybrid intrusion detection and prevention architectures
• real-time threat intelligence integration into IDS/IPS
• intrusion detection in cloud environments
• intrusion prevention in IoT (Internet of Things) networks
• reinforcement learning for intrusion detection and prevention
• generative adversarial networks (GANs) in intrusion detection
• explainable AI techniques for IDS and IPS
• deep learning models for anomaly detection in network traffic
• transfer learning approaches for IDS and IPS
• federated learning for distributed intrusion detection systems
• ensemble methods in intrusion detection and prevention
• deep reinforcement learning for adaptive IPS policies
• cognitive models for human-in-the-loop intrusion analysis
• adversarial machine learning for robust IDS and IPS
• graph-based intrusion detection and prevention systems
• reinforcement learning for dynamic firewall policy management
• explainable anomaly detection models for network intrusion detection
• reinforcement learning for self-adaptive intrusion response
• interpretability techniques for neural network-based IDS and IPS models