We are seeking full papers, short papers, posters, demos and work-in progress papers in cyber security for the networking domain.

The driving theme at CSNet 2024 is “AI for Cybersecurity”, focusing on its applications in emerging networks and systems. This encompasses addressing the Challenges and Opportunities of AI to reinforce security and privacy in Next-Generation Technologies. 

The technological disruption is impacting society and leading to a new industrial revolution. This social and industrial change presents new technological environments constituted by ubiquitous systems and large amounts of information, which requires a change in the way how cybersecurity is applied. Using big data, data science, and AI/machine learning/deep learning models, strengthens the cognitive skills of security analysts to face new forms of cybersecurity attacks. This new trend, called cognitive security, poses new challenges for researchers and companies to seek proactive security proposals according to this technological change. 

AI, particularly machine learning (ML), is increasingly indispensable in the realm of cybersecurity for emerging networks and applications. With the emergence of new use cases such as threat detection, autonomous systems, and technologies like the Internet of Things (IoT), drones, and robotics, the vision of AI-driven cybersecurity is becoming more defined. Advanced deep learning techniques including transfer learning, federated learning, and large language models (LLM) play a pivotal role in fortifying cybersecurity measures, optimizing threat responses, and enhancing overall network security. Moreover, these methods might facilitate the development of adaptive and resilient security frameworks for operators.

CSNET 2024 aims to cover a broad spectrum of state-of-the-art and emerging topics related to AI-driven cybersecurity for emerging systems, networks, and applications. Anticipated to draw a significant number of high-quality submissions, the conference will foster cutting-edge research discussions (full/short papers) among numerous pioneering academic researchers/scientists and industrial engineers/leaders from around the world in the field of AI for cybersecurity.

The CSNET 2024 program will include several symposia, workshops, invited presentations, special sessions, and pioneering keynote speakers. Prospective authors are encouraged to submit original technical papers of up to 6 pages in length using the corresponding EDAS link.

During this conference, experts from academia and various industry sectors will explore the opportunities afforded by the latest AI techniques in cybersecurity. Additionally, they will discuss the challenges associated with integrating AI into the design and operation of next-generation networks, applications, drones, and robotics, thereby ensuring robust and comprehensive protection against evolving cyber threats.

Authors are welcome to submit original papers (not published before and/or simultaneously to another venue) with topics that include but are not limited to:

    Advanced AI for Cybersecurity
    AI-based Cybersecurity for Next-Generation Technologies
    Challenges and Opportunities in AI-driven Security
    Emerging AI Threats and Countermeasures
    Privacy Preservation in AI-driven Security
    Privacy-preserving AI for Surveillance and Monitoring
    Cognitive Security and Adaptive Defense Mechanisms
    Advanced Deep Learning Techniques for Cyber Defense
    Blockchain
    Cloud Security
    Cognitive Cyber Security
    Cyber-attacks & defense
    Cyber-Physical System (CPS) Security
    Cybersecurity and Human Rights
    Data Center Network Control, Security, and Optimization
    Decentralized Security
    Resilient Networks and Systems
    Secure Protocol Design and Key Management
    Secure Architecture Design
    Secure Network Design
    Security Policies Design
    Security for the Internet of Things
    Security in Fog/edge Computing
    AI-driven Intrusion Detection and Prevention Systems
    AI-driven Security Monitoring and Anomaly Detection
    Cyber Threat Intelligence and Information Sharing
    AI-based Cybersecurity for IoT and Fog/edge Computing
    Adversarial Machine Learning and AI Security
    AI for Cyber Resilience and Incident Response Strategies
    AI for Biometric Security
    AI for Secure Software Development and DevSecOps
    AI-enabled Threat Hunting and Cyber Forensics
    AI-enabled Ethical Hacking
    AI for Blockchain Technology
    AI-based Secure Cloud Computing and Data Protection
    AI-based  Cybersecurity in Smart Cities/Grids and Urban Environments
    AI for Secure Authentication and Access Control Mechanisms
    AI-powered Threat Modeling and Risk Assessment
    AI-driven Security Automation and Orchestration
    Secure AI Model Training and Adversarial Mitigation
    AI-driven Security Operations Center (SOC)
    Secure Federated Learning
    Federated Learning cybersecurity solutions
    LLM-based Anomaly Detection
    LLM-based Malware Detection and Classification
    Secure Deployment of LLM-based Security Solutions
    AI for Hardware-Based Attacks
    AI-based Vulnerability Assessment and Patch Prioritization
    Zero-Day Attack Detection Using AI-based Techniques
    Ethical and Regulatory Considerations in AI-based Security
    Reinforcement Learning-based Cybersecurity Solutions

Submitted papers are encouraged to address novel technical challenges or industrial and standard aspects of the key technologies for sustainable and intelligent AI cybersecurity solutions.