Información de la conferencia

IEEE TPS 2026: IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications

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Día de Entrega:
2026-08-15 Faltan 46 días
Fecha de Notificación:
2026-09-20
Fecha de conferencia:
2026-11-04
Ubicación:
San Jose, California, USA
Ediciones:
8
Vistas: 17131   Seguidores: 2   Asistentes: 0

Solicitud de Artículos

IEEE TPS 2026 (IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications) is an academic conference held in San Jose, California, USA on 2026-11-04. The paper submission deadline is 2026-08-15. Acceptance notifications are sent on 2026-09-20.

Recent advances in computing and information technologies such as IoT, mobile Edge/Cloud computing, cyber-physical-social systems, Artificial Intelligence / Machine Learning / Deep Learning, etc., have paved way for creating next generation smart and intelligent systems and applications that can have transformative impact in our society while accelerating rapid scientific discoveries and innovations. Such newer technologies and paradigms are getting increasingly embedded in the computing platforms and networked information systems/infrastructures that form the digital foundation for our personal, organizational and social processes and activities. It is increasingly becoming critical that the trust, privacy and security issues in such digital environments are holistically addressed to ensure the safety and well-being of individuals as well as our society. IEEE TPS-ISA is an international multidisciplinary forum for presentation of state-of-the art innovations, and discussion among academic, industrial researchers, and practitioners on issues related to trust, privacy and security in emerging smart and intelligent systems and applications. List of Topics Topics of interest include, but are not limited to: Large Language models Social computing Machine learning with graphs Foundational, theoretical models for trust, privacy and security in emerging applications Trusted AI, Machine Learning and Deep Learning Privacy preserving Machine Learning and Deep Learning Trustworthy, safe and resilient intelligent systems Trusted, privacy-conscious and secure systems, applications and networks/infrastructures Security and privacy in IoT and Cyber-physical-human systems Trustworthy and secure Human-Machine collaboration Access and trust management/negotiation, and secure information flow/sharing Bio-inspired approaches to trust, privacy and security Game theoretical approaches to trust, privacy, and security Adversarial machine learning Trust, privacy and security for big data systems, applications and platforms Trust, privacy and security for smart cities and urban computing Machine Learning / Deep learning over encrypted data Usability and human factors for trust, privacy and security Tools, techniques and metrics for trust, privacy and security Anonymization techniques and differential privacy for emerging intelligent applications Trust, privacy and security approaches for services computing: microservices, service-oriented architectures, service composition and orchestration Blockchain and Distributed-ledger technologies Blockchain/Distributed ledger for e-commerce, mobile commerce and intelligent applications Bias, fairness and integrity/robustness of algorithmic machine / AI algorithms Trusted, privacy-aware and secure interoperation of interacting/collaborative systems Threat models and attack modeling for AI/ML and applications Identification/Detection of spam, phishing, malware and APTs Cryptographic approaches and secure multiparty computation Privacy-preserving data mining and big data analytics Application of AI/ML and Deep learning for trust, privacy and security Trust, privacy and security in edge/cloud computing, social computing Safe and trusted autonomous vehicles/UAVs, robotics Trust, security and safety in supply-chain environments and critical infrastructures Data quality/credence, privacy and provenance Trust in social media – disinformation/misinformation Risk metrics and measurements, assessment/analysis and mitigation Insider threat modeling, analysis and mitigation; behavioral modeling for security and trust Digital payments and cryptocurrencies; Secure and trustworthy e-commerce and mobile commerce Trust negotiation and/or propagation in interacting systems of systems, multi-agent systems, social networks.
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