Since the first successful edition in Rio de Janeiro (Brazil, 2017) and all subsequent editions (2018 in Paris, 2019 in Quito, 2020 in Lausanne, 2021 in Abu Dhabi, 2022 in Rio de Janeiro, 2023 in Montreal, 2024 in Paris, and 2025 in Abu Dhabi) the CSNet conference has aimed to bring future visions for creating even greater value to all corners of the cybersecurity research society.

This year, CSNet 2026 will center around the “Cybersecurity and Resilient Networking for Emerging Systems in AI Era” theme, focusing on advancing security and resilience in emerging networks and digital systems. This encompasses addressing the evolving challenges and opportunities associated with protecting next-generation technologies and ensuring the security and privacy of increasingly interconnected infrastructures. As digital ecosystems continue to expand in scale and complexity, strengthening cybersecurity foundations is essential to safeguarding critical services and sustaining trust in modern information systems.

The growing interconnection of cloud platforms, edge environments, Internet of Things (IoT) deployments, mobile infrastructures, and cyber-physical systems has significantly transformed the threat landscape. Contemporary cybersecurity solutions must address sophisticated and persistent attacks while supporting scalability, reliability, and operational continuity. From proactive threat detection and risk assessment to adaptive defense mechanisms and resilient system architectures, modern approaches aim to enhance both the effectiveness and sustainability of security measures. These efforts contribute to the development of robust defense strategies capable of protecting digital infrastructures against increasingly advanced and coordinated cyber threats.

Artificial Intelligence (AI) is reshaping both the defensive and offensive dimensions of cyberspace. On one hand, AI enables scalable threat detection, predictive analytics, automated response, and intelligent security orchestration. On the other, AI systems themselves are increasingly targeted through adversarial attacks, model manipulation, data poisoning, and privacy leakage. This dual role of AI—as both a security enabler and a security target—demands rigorous research at the intersection of machine learning, system security, cryptography, privacy engineering, and governance.

Bringing together researchers and industry professionals at CSNet 2026 is essential for creating a secure digital future. Collaboration between academia and industry is vital to driving innovation and ensuring that theoretical research translates into practical, real-world applications. Researchers bring cutting-edge ideas and theoretical insights, while industry professionals provide practical perspectives and highlight the pressing challenges faced in real-world scenarios. Together, they can forge new pathways and develop comprehensive solutions that address both current and future cybersecurity challenges.

CSNet 2026 seeks contributions in the cybersecurity field, raising footprints with tremendous impact in many sectors of society (e.g., development, innovation, teaching, and practice) in the form of full papers, short papers, posters, demos, work-in-progress papers, and tutorials. We are particularly interested in innovative solutions and breakthrough ideas that can shape the future landscape of cybersecurity.

Authors are welcome to submit original papers (not published before and/or not simultaneously submitted 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
    Human-AI collaboration in Security Operation Centers (SOC)

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