The 1^st International Conference on Artificial Intelligence and Information Security (AIIS) invites original and unpublished research contributions from academia, industry, and research organizations worldwide. With the overarching theme “Enhancing the Future: AI and Cybersecurity Trends in Academics, Industry, and Research”, this conference seeks to explore the convergence of intelligent systems and security mechanisms in shaping a resilient digital future.

We welcome high-quality submissions that present novel ideas, practical solutions, theoretical models, and innovative implementations addressing the multifaceted challenges and opportunities at the intersection of artificial intelligence and information security. AIIS’26 aims to serve as a dynamic platform for researchers, developers, educators, practitioners, engineers, and policy-makers to share insights, exchange experiences, and foster collaborations.

Conference Themes

BUT NOT LIMITED TO...

THEME 1

Artificial Intelligence & Machine Learning

THEME 2

Cyber Security and Information Privacy

THEME 3

Cloud, IoT, and Edge Security

THEME 4

Blockchain and Cryptographic Techniques: Threat Detection and Prevention

THEME 5

Secure Authentication and Access Management

Scope of the Conference (Thrust Area)

Submissions are solicited in, but not limited to, the following thematic areas:

• Artificial Intelligence & Machine Learning
  1. Supervised and unsupervised learning models
  2. Deep learning and neural networks
  3. Reinforcement learning and autonomous agents
  4. Explainable and interpretable AI
• AI in Cybersecurity
  1. AI-driven threat detection and prediction
  2. Intrusion detection systems (IDS)
  3. Intelligent malware analysis
  4. Trustworthy and secure AI systems
• Data Privacy and Ethics
  1. Privacy-preserving machine learning
  2. AI fairness, bias mitigation, and accountability
  3. Legal and ethical implications of AI in security
• Cyber Threat Intelligence
  1. Advanced persistent threats (APT) detection
  2. Threat modeling and adversarial learning
  3. Behavioral analysis and anomaly detection
• Cloud, IoT, and Edge Security
  1. Secure edge computing architectures
  2. AI-based IoT vulnerability assessment
  3. Cloud-native security strategies
• Blockchain and Cryptographic Techniques
  1. Blockchain for authentication and access control
  2. Smart contracts and secure transaction systems
  3. Post-quantum cryptography and quantum-safe AI
• Quantum Computing and AI
  1. Quantum machine learning models
  2. Cryptographic challenges in the quantum era
  3. Quantum-enhanced cybersecurity frameworks
• Digital Forensics and Incident Response
  1. AI-enabled forensic analysis tools
  2. Threat hunting and digital investigation
  3. Automation in incident response
• Secure Software and Systems Design
  1. AI-assisted secure coding practices
  2. Static/dynamic analysis using machine learning
  3. Software vulnerability detection and patching
• Case Studies and Industrial Applications
  1. AI solutions in financial cybersecurity
  2. Healthcare data security and compliance
  3. Smart city security frameworks