IEEE TPS 2026
The 8th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications
Nov. 4-6, 2026, San Jose, CA, USA
Co-located with IEEE CIC 2026, IEEE CogMI 2026, IEEE RISC 2026.
The 8th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications
Nov. 4-6, 2026, San Jose, CA, USA
Co-located with IEEE CIC 2026, IEEE CogMI 2026, IEEE RISC 2026.
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.
Topics of interest include, but are not limited to:
- Large Language and foundation models – trust, safety, security, privacy, and resilience
- Security and robustness of multimodal and vision-language models
- Jailbreaks, prompt injection (direct and indirect), and guardrail evasion in LLMs
- Memorization, membership inference, model/data extraction, and PII / system-prompt leakage
- Retrieval-augmented generation (RAG) security, knowledge-base poisoning, and machine unlearning
- Secure and trustworthy agentic AI: tool/function-call abuse, sandboxing, and least-privilege execution
- Multi-agent security; agent-to-agent communication, orchestration, and protocol security (e.g., MCP)
- Identity, authentication, and delegated access control for AI agents
- Agent memory and context integrity, goal manipulation, and human oversight of autonomous systems
- Trustworthy Artificial General Intelligence and Superintelligence: safety, security, control, and alignment
- Social computing and social cybersecurity
- AI / Machine learning security, privacy, and trust
- Foundational, theoretical models for trust, privacy, and security in emerging applications
- Safe and Trustworthy AI, Machine Learning, and Deep Learning
- AI assurance, auditing, red-teaming, evaluation, and benchmarking
- Conformance with AI risk frameworks and regulation (e.g., NIST AI RMF, EU AI Act); open-weight and frontier-model risk
- Privacy-preserving machine learning and deep learning
- Federated and decentralized learning: security, privacy, and robustness
- Confidential computing, trusted execution environments, and secure enclaves for AI
- Synthetic data: utility, privacy risk, and governance
- Trustworthy, safe, and resilient intelligent systems
- Trusted, privacy-conscious and secure systems, applications and networks/infrastructures
- Post-quantum cryptography and crypto-agility for AI-enabled systems and infrastructures
- Security and privacy in Smart IoT and Cyber-physical-human systems
- Trustworthy and secure Human-Machine collaboration
- Access and trust management/negotiation, and secure information flow/sharing in Intelligent systems
- Bio-inspired approaches to trust, privacy, and security
- Game theoretical approaches to trust, privacy, and security
- Adversarial machine learning
- AI/ML supply-chain security: poisoned/backdoored weights, model and dataset provenance, model cards, and AI bills of materials (AIBOM)
- 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
- Security, privacy, and trust in Blockchain and Distributed-ledger technologies
- Blockchain/Distributed ledger for e-commerce, mobile commerce, and intelligent applications
- Bias, fairness, and integrity/robustness of algorithmic machine learning / 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 using AI
- AI/LLM-assisted vulnerability discovery, autonomous cyber defense, and offensive-AI / dual-use risks
- Cryptographic approaches and secure multiparty computation for AI
- 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 trustworthy autonomous and embodied agents: autonomous vehicles, UAVs, and robotics
- Trust, security, and safety in supply-chain environments and critical infrastructures
- Data quality/credence, privacy, and provenance in AI-driven systems
- Provenance, watermarking, and fingerprinting of AI-generated content; deepfakes, synthetic identity, and AI-enabled fraud
- Trust in social media – AI-enabled disinformation and misinformation at scale
- Risk metrics and measurements, assessment/analysis, and mitigation in AI-enabled systems
- 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
We invite original research papers that have not been previously published and are not currently under review for publication elsewhere. Papers submitted to Research track should be up to 10 pages, anonymously in the standard two column IEEE proceedings format, excluding the bibliography, well-marked appendices, and supplementary material. which can be found at IEEE Manuscript Templates for Conference Proceedings . Authors should not change the font or the margins of the IEEE format. Papers should avoid revealing authors’ identity in the text. When referring to their previous work, authors are required to cite their papers in the third person, without identifying themselves. The papers should be submitted at the research track of the conference in EasyChair.
We invite original research vision papers that have not been previously published and are not currently under review for publication elsewhere. Vision contributions should focus on blue-sky ideas and research vision in the area that at least one of the lead senior authors are known for. Vision paper can be as short as 2 pages but should be no longer than 10 pages in the standard two column IEEE proceedings format, which can be found at IEEE Manuscript Templates for Conference Proceedings . The papers should be submitted at the vision track of the conference in EasyChair.
We invite original industry papers that have not been previously published and are not currently under review for publication elsewhere. At least one co-author must be affiliated with industry or Government organizations, such as labs in DoE, DoD, NIH, NSA Labs. Papers submitted to Regular or Industry/Gov track should be no longer than 10 pages in the standard two column IEEE proceedings format, IEEE Manuscript Templates for Conference Proceedings . The papers should be submitted at the industry/gov track of the conference in EasyChair.
Submission Rounds: There are two submission rounds to IEEE TPS 2026. Authors who submit in the first round may revise and resubmit their papers in the second round if their papers are not accepted initially. It is also possible to submit directly to Round 2; however, in that case, there won't be an opportunity for resubmission.
Authors should note the following key points regarding use of large language models (LLMs) and other generative AI tools in the preparation of their submissions. These points are meant to complement IEEE's policy on AI generated text, available here: IEEE Submission Policies.
Use of AI tools solely for minor copy-editing or grammar/clarity improvements applied to the authors' own text does not require disclosure.AI Disclosure: We used [Tool Name] to assist with [Brief Description of Use]. The tool materially affected [Sections X and Y]. More details can be found in [Section Z]. The authors verified the correctness and originality of all content including references.
Proposals for half-day or full day workshops that focus on IEEE TPS 2026 related themes are solicited. Workshop proposals should be at most 6 pages, including a biographical sketch of each instructor, and submitted to the EasyChair.
Proposals for panel discussions that focus on future visions relevant to Trust, Privacy and Security are preferred. Potential panel organizers should submit a panel proposal of at most three pages, including biographical sketches of the proposed panelists and questions to be asked to the Executive Chairs.
Proposals for full and half-day tutorials are solicited. Tutorials are intended to enhance the technical program, and as such they should be relevant to the conference related themes. Potential tutorial presenters should submit a tutorial proposal of at most three pages, including: description of potential audience and background knowledge expected from the audience, if any; tutorial description; biographical sketch(s) of presenter(s).
IEEE Policy and professional ethics require that referees treat the contents of papers under review as privileged information not to be disclosed to others before publication. It is expected that no one with access to a paper under review will make any inappropriate use of the special knowledge, which that access provides. Contents of abstracts submitted to conference program committees should be regarded as privileged as well, and handled in the same manner. The Conference Publications Chair shall ensure that referees adhere to this practice.
Organizers of IEEE conferences are expected to provide an appropriate forum for the oral presentation and discussion of all accepted papers. An author, in offering a paper for presentation at an IEEE conference, or accepting an invitation to present a paper, is expected to be present at the meeting to deliver the paper. In the event that circumstances unknown at the time of submission of a paper preclude its presentation by an author, the program chair should be informed on time, and appropriate substitute arrangements should be made. In some cases it may help reduce no-shows for the Conference to require advance registration together with the submission of the final manuscript.
We would like to solicit papers that promote visionary ideas and blue sky thinking in areas aligned with the conference themes. These papers are expected to spark intense discussions and newer research directions/insights through potentially disruptive, controversial, or highly cross-disciplinary ideas that look forward to Trust, Privacy and Security areas for the next 10 years and beyond. Ideas that are just being conceived, not fully developed, far from experimentally evaluated, or out-of-the box are highly encouraged. The papers should follow the same format as the regular conference papers and can be up to 10 pages.
We would like to solicit papers that focus on design, implementation and deployment of solutions related to Trust, Privacy and Security within the industrial or government environments. The papers submitted to this track are expected to advance practical and applied research focused on the use of TPS technologies, and real-world networks, systems applications.
The Industry/Government Track will include papers selected through a separate program committee. Authors must clearly indicate sub-areas their papers are to be evaluated in because distinct criteria may be used for reviewing different category of submissions:
Deployed systems that aim to provide real practical value to industry, Government, or other organizations, or communities. The papers should point out how the deployed system explicitly address TPS issues or describe either qualitatively (lessons learnt, deployment experiences, etc.) or quantitatively how Trust, Privacy and Security issues are addressed in smart, intelligence systems and applications.
Newer models and mechanisms or innovative solutions related to Trust, Privacy and Security in networks, systems and applications are expected here. The authors should clearly demonstrate value and interest to Industry, Government of society (e.g., scientific or medical professions; critical infrastructures). Papers that describe infrastructure development and deployment that enables the large-scale deployment of trusted, safe, secure and privacy-aware technologies/applications or their validation are also in these areas.
IEEE TPS will feature a Best Paper award and a Best Student Paper award (to be selected by the program committee/best paper award team). A paper is eligible for the Best Student Paper award if the first author is a full-time student at the time of submission. A partial travel grant or cash award may be offered to the winner student depending on fund availability.
Congratulations on your paper's acceptance! Please follow these instructions carefully to prepare and submit your camera-ready version. All submissions must be made through the IEEE Conference Publishing Services (CPS) Author Kit system, which ensures compliance with formatting and publication standards.
Use the IEEE CPS Author Kit submission site to complete the following steps in order:
