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AIM & SCOPE


The emerging IoT revolution promises to impact almost every aspect of modern society. In an IoT setting, sensors help create a fine-grained digital representation of the evolving physical world. This can be used to implement new functionalities and/or bring transformative improvements to existing systems. Central to IoT applications is the data management technology that can represent, store, transform, and query sensor data. Given the importance of IoT, the data management community has been focusing on meeting the volume, velocity, veracity, variety, and virtualization needs of IoT data.

However, the fine-grained monitoring enabled by IoT also raises significant concerns about the data collector being able to infer properties such as religious beliefs, gender, and personal habits of individuals among others, which individuals may not be comfortable sharing. The existing behavior of IoT devices and systems contradicts the increasing expectations of privacy with respect to the new legislations emerging worldwide (such as Europe’s GPDR and California’s CCPA). The success and adoption of IoT data management systems depends on integrating privacy, security, and trust protections into them to protect the user data.

The goal of this workshop is to help bridge the gap between two research communities ---- Security and Privacy Researchers, IoT Data management Researchers --- both from industry and academia. Additionally, the workshop would be an opportunity to bring privacy legislators and developers of modern data management systems into this important conversation.



CALL FOR PAPERS


Download CFP

TOPICS OF INTEREST


Topics of interest include, but are not limited to:

* Secure hardware for IoT data management
* Model-based security systems engineering
* Understanding dependencies among security, reliability,and safety in CPS/IoT
* High-assurance security architectures
* Intrusion and anomaly detection
* Secure and privacy-preserving sensor data outsourcing
* Privacy-by-design of IoT data management systems
* Differentially private computing
* Privacy-preserving machine learning and federated learning and analytics
* Privacy regulations (GDPR, CCPA, CalOPPA) and their impact on IoT systems
* Privacy-Preserving Data Analysis in IoT Systems
* Inference control and access control policies
* Authentication
* Blockchain-based systems
* Identity and access management
* Security, privacy, and utility metrics
* Application/use-cases in healthcare, environment, transportation, energy, etc.


SUBMISSION GUIDELINES

We encourage researchers from industry and academia to submit original works to the submission site https://cmt3.research.microsoft.com/ASTRIDE2023. Submitted papers must represent original material that is not currently under review in any other conference or journal, and has not been previously published. All paper submissions should be a maximum length of six (6) printed pages in IEEE format without references (templates are available at the ICDE 2023 submission guidelines page). Two (2) additional pages will be allowed in the camera ready submission to incorporate comments from the reviewers. Accepted papers will be selected for oral presentation based on peer review. Submissions are not double-blind; the submitted paper should include author names and affiliations. All accepted papers will appear in the formal Proceedings of the Conference Workshops.



Submit

Paper submission deadlines:

December 12, 2022 (11:59PM PST)

Notification:

January 17, 2023

Camera-ready:

February 10, 2023

ORGANIZATION


Organizers


Xi He

Assistant Professor, University of Waterloo

Primal Pappachan

Postdoctoral Scholar, Pennsylvania State University

Shantanu Sharma

Assistant Professor, New Jersey Institute of Technology

Roberto Yus

Assistant Professor, University of Maryland, Baltimore County


Program Comittee


  • Amit Kumar Sikder, Georgia Institute of Technology, USA
  • Amrita Roy Chowdhury, UC San Diego, USA
  • Anna Squiccarini, Penn State University, USA
  • Asha Abraham, HubSpire, USA
  • Chang Ge, University of Minnesota, USA
  • Chenxi Qiu, University of North Texas, USA
  • Himanshu Gupta, IBM, India
  • Ioannis Koutis, New Jersey Insitute of Technology, USA
  • Jelle Hellings, McMaster University, Canada
  • Johes Bater, Tufts University, USA
  • Mohammad Javad Amiri, University of Pennsylvania, USA
  • Philip Derbeko, Dell EMC, Israel
  • Pietro Colombo, University of Insubria, Italy
  • Reza Tourani, Saint Louis University, USA
  • Sarvesh Panday, Banaras Hindu University, India
  • Suyash Gupta, UC Berkeley, USA
  • Uday Kiran Rage, University of Aizu, Japan
  • Yang Cao, Hokkaido University, Japan