TAICS-2027.

Aim and Scope

TAICS-2027welcomes original research papers, case studies, innovative applications, and industry-driven contributions from researchers, academicians, practitioners, policymakers, and technology leaders. The conference aims to provide a multidisciplinary platform for discussing recent advances, challenges, and future directions in Artificial Intelligence Computing. It seeks to foster collaboration among experts working at the intersection of intelligent computing, data-driven technologies, computational intelligence, and emerging digital ecosystems.

TAICS-2027 invites original work from the following list of topics (but is not limited to):

Topics

1. Trustworthy, Responsible and Ethical AI

• Trustworthy Artificial Intelligence
• Responsible Artificial Intelligence
• Ethical AI and AI Ethics
• AI Safety and Reliability
• AI Transparency and Accountability
• AI Fairness, Bias and Discrimination
• Human-Centered and Human-Values-Based AI
• AI Governance and Assurance
• AI Risk Management
• AI Compliance and Regulatory Frameworks
• Human Oversight and Meaningful Human Control
• AI Alignment and Value Alignment
• Responsible AI Lifecycle Management
• Societal Implications of Trustworthy AI
• Standards and Frameworks for Trustworthy AI

2. Secure and Robust Artificial Intelligence

• AI Security and Secure-by-Design AI
• Secure Machine Learning
• Robust Artificial Intelligence
• Adversarial Machine Learning
• Adversarial Attacks and Defences
• Data Poisoning and Model Poisoning
• Evasion and Adversarial Examples
• Model Extraction and Model Inversion
• Backdoor Attacks and Defence
• AI Model Integrity and Protection
• Robustness Evaluation and Stress Testing
• AI Red Teaming and Security Testing
• Resilient AI Systems
• AI Supply Chain Security
• Security of AI Development and Deployment Pipelines

3. Explainable, Interpretable and Auditable AI

• Explainable Artificial Intelligence (XAI)
• Interpretable Machine Learning
• Explainability for Deep Learning
• Explainable Generative AI
• Explainable Cybersecurity Systems
• Model Transparency and Interpretability
• AI Decision Traceability
• Algorithmic Accountability
• AI Auditing and Assurance
• Model Documentation and Reporting
• AI Risk and Impact Assessment
• Uncertainty Quantification in AI
• Confidence and Reliability Estimation
• Explainability for High-Stakes AI
• Human-Centered AI Assurance

4. Privacy-Preserving AI and Data Security

• Privacy-Preserving Artificial Intelligence
• Privacy-Preserving Machine Learning
• Federated Learning and Secure Federated AI
• Differential Privacy
• Secure Multi-Party Computation
• Homomorphic Encryption and AI
• Confidential Computing for AI
• Data Anonymization and De-Identification
• Data Protection and AI
• Privacy Attacks and Defences
• Membership Inference Attacks
• Model Inversion Attacks
• Data Leakage and Information Exposure
• Secure Data Sharing and Collaboration
• Privacy-Preserving Generative AI

5. Generative AI and Large Language Model Security

• Security of Generative AI
• Large Language Model Security
• Secure Foundation Models
• Prompt Injection and Jailbreaking
• Adversarial Prompting
• LLM Data Leakage and Privacy
• Model Manipulation and Poisoning
• Retrieval-Augmented Generation Security
• Security of AI Agents and Agentic AI
• AI Agent Authentication and Authorization
• Generative AI Threat Detection
• Deepfakes and Synthetic Media Security
• Malicious Use of Generative AI
• LLM Red Teaming and Security Evaluation
• Secure and Responsible AI Content Generation

6. AI for Cybersecurity and Intelligent Cyber Defence

• Artificial Intelligence for Cybersecurity
• Machine Learning for Cyber Threat Detection
• AI-Based Intrusion Detection and Prevention
• Intelligent Security Information and Event Management
• AI-Based Malware Detection and Classification
• Ransomware Detection and Defence
• Phishing and Social Engineering Detection
• Anomaly and Behavioural Detection
• AI-Based Vulnerability Detection
• Automated Threat Detection and Response
• AI-Driven Security Operations Centres
• Cyber Threat Intelligence and AI
• AI-Based Fraud and Financial Crime Detection
• Predictive Cybersecurity Analytics
• Autonomous and Adaptive Cyber Defence

7. Cybersecurity, Networks and Critical Infrastructure

• Network Security and AI
• Secure Communication Systems
• Network Intrusion Detection
• Wireless and 5G/6G Security
• Internet of Things Security
• Edge and Cloud Security
• Cloud-Native Security
• Zero-Trust Architecture
• Identity and Access Management
• Authentication and Authorization
• Critical Infrastructure Cybersecurity
• Industrial Control Systems Security
• Operational Technology Security
• Smart Grid and Energy Infrastructure Security
• Cyber-Physical Systems Security
• Digital Twin Security

8. Cyber Threats, Digital Forensics and Incident Response

• Cyber Threat Intelligence
• Advanced Persistent Threats
• Malware and Ransomware Analysis
• Botnets and Emerging Cyber Threats
• Cyber Attack Detection and Attribution
• Digital Forensics
• AI-Assisted Digital Forensics
• Network and Memory Forensics
• Cyber Incident Response
• Security Incident Investigation
• Cyber Attack Reconstruction
• Automated Threat Hunting
• Security Operations and Cyber Resilience
• Cyber Risk Assessment
• Cybersecurity Situational Awareness
• Deception Technologies and Honeypots

9. Blockchain, Cryptography and Emerging Security Technologies

• Applied Cryptography and Cybersecurity
• Post-Quantum Cryptography
• Quantum-Safe Security
• Blockchain Security
• Distributed Ledger Security
• Smart Contract Security
• Decentralized Identity and Security
• Secure Digital Identity
• Hardware-Assisted Security
• Trusted Execution Environments
• Secure Hardware and Embedded Systems
• Blockchain and AI Security
• Quantum Computing and Cybersecurity
• Secure Edge and Distributed AI
• Emerging Security Architectures

10. AI Governance, Cyber Resilience and Future Security

• AI Governance and Cybersecurity
• AI Regulations, Policies and Standards
• AI Security Governance
• Cybersecurity Governance and Risk Management
• AI and Cybersecurity Compliance
• Security of Autonomous and Agentic AI
• Cyber Resilience of AI Systems
• AI Safety and Cyber Risk
• Security of Autonomous Systems and Robotics
• AI-IoT Security
• Security of Smart Cities and Connected Environments
• Cybersecurity for Digital Transformation
• Organizational AI and Cybersecurity Readiness
• Cybersecurity Workforce and Skills
• Human Factors in Cybersecurity
• Future of Trustworthy AI and Cybersecurity
• Societal and Global Dimensions of AI Security