The 2nd IEEE Workshop on Healthcare and Medical Device
Security, Privacy, Resilience, and Trust
(IEEE HMD-SPiRiT)
San Jose, CA, USA
Co-located with IEEE CIC 2026, IEEE CogMI 2026, IEEE TPS 2026, IEEE RISC 2026.
Rapid advances in data-centric and AI technologies, as well as computing and communication technologies more broadly, are presenting us with unprecedented opportunities to revolutionize healthcare services, drug discovery, advanced disease diagnostics, and precision or personalized medicine, just to name a few. Similarly, the proliferation of sensors and medical devices, such as wearable, implantable, or neuromorphic devices, which are increasingly integrated into our hyperconnected cyber environments in healthcare settings, further amplifies such opportunities. At the same time, there are growing security and privacy concerns due to the growing reliance of healthcare applications and services on such increasingly complex and hyperconnected computing and information infrastructures. Ensuring security, privacy, resilience and trust of the healthcare ecosystem/sector – one of the 16 critical infrastructures in the USA – including that of health IT infrastructures and services, medical device and sensor ecosystem, clinical diagnostics and analytics, healthcare application ecosystem, etc., are critical for the overall health and well-being of individuals, communities, and society-at-large. Various security and privacy techniques, such as multiparty computation, homomorphic and functional encryption, differential privacy or other statistical information disclosure techniques, federated learning, data use and access control models, trusted execution environments, private information retrieval, etc., show tremendous promise to address data access, sharing, and usage challenges. Preventative, proactive, and defensive mechanisms to address insider and external threats, and building resilience against adversarial attacks, and establishing trustworthiness of the healthcare ecosystem are increasingly becoming very critical.
The IEEE Workshop on Healthcare and Medical Device Security, Privacy, Resilience and Trust (HMD-SPiRiT) aims to bring together researchers and practitioners to foster foundational and applied research, and explore interdisciplinary socio-technical innovations to address the challenges related to security, privacy, resilience and trust of the healthcare sector and its entire ecosystem, which encompasses devices and sensors, data and digital infrastructure , AI and advanced analytics, public health and bioinformatics, considering broader concerns of the stakeholders such as healthcare providers, consumers, administrators, clinicians, health scientists and researchers.
We solicit research and work-in-progress submissions that are up to 10 pages max. All submissions must follow the same submission guidelines and instructions for the main conference (IEEE TPS), with the IEEE two-column conference format. Templates are available from the IEEE website.
Submissions must be made through EasyChair: IEEE TPS. Select the track: "IEEE Workshop on Healthcare and Medical Device Security, Privacy, Resilience and Trust (HMD-SPiRiT)".
Each submission will be reviewed by at least two members in the workshop's Program Committee. Accepted papers will be included in the IEEE TPS 2026 Proceedings, published by IEEE, and will be included in IEEE Xplore. At least one author must register and attend to present the work.
Topics of interest include, but are not limited to:
- Secure, privacy-preserving healthcare data sharing
- Synthetic data generation for electronic health records and other medical data
- Distributed model training and learning frameworks on healthcare data
- Privacy protection and security of medical devices (e.g., sensors, embedded, wearable, and neuromorphic devices) – understanding, assessing, and defending against or mitigating both insider and outsider threats
- Security, privacy, and resilience of cyber-physical healthcare infrastructures and environments
- Secure, privacy-preserving, and/or bias-free AI and analytics for healthcare, including LLMs and agentic AI
- Trust modeling and Trustworthy frameworks for healthcare infrastructures (e.g., Health Information Exchanges) and applications (mHealth, eHealth, health-focused social networking apps, etc.)
- Blockchain or Distributed Ledger Technologies (DLTs) for digital health
- Secure and privacy-preserving technologies for public health
- Social, economic, and behavioral research to enhance secure and privacy-aware healthcare applications
- Accountability, transparency, ethics, and explainability in Healthcare IT
- Techno-policy frameworks for resilience and assurance of healthcare and medical device systems, and applications
- Data protection and privacy laws and policies, and regulatory compliance and liabilities in digital healthcare
- Differential privacy and other formal privacy-enhancing technologies (PETs), including secure multiparty computation, homomorphic and functional encryption, trusted execution environments, and private information retrieval for healthcare and biomedical data.
- Privacy and security of genomic and multi-omics data, including secure/federated GWAS, privacy-preserving biomedical queries, and genomic data-sharing protocols.
- Privacy and security attacks on healthcare AI and data releases, including membership inference, model memorization and extraction, re-identification and linkage attacks and defenses.
Please contact Dr. James Joshi (jjoshi@pitt.edu) for more information.