CALL FOR PAPERS

Embedded systems have become pervasive in modern society, and their diffusion is still growing rapidly, apparently without limits. Applications fields are countless, ranging from automotive, telecommunications, digital healthcare, smart cards, military, satellites, computer networking, digital consumer electronics, Internet of Things, nano- or bionano-things, and so on.

The huge amount of data gathered and processed by such systems often contains Personal Identifiable Information (PII) of users, which must be protected according to the recommendations of the EU's General Data Protection Regulation (GDPR).

It is essential that users can control when and how their personal data is collected, processed, and communicated by embedded systems. It should come as no surprise that privacy has been acknowledged as an important new dimension in nowadays embedded systems design.

Together with classic embedded design metrics like area, performance and power consumption, privacy is becoming paramount too. Novel privacy protection approaches (differential privacy, k-anonymity, homomorphic encryption to name a few) promise to revolutionize the way users can protect their data, but it is still unclear how these approaches can be applied in an efficient and effective manner in embedded systems.

The HTESP workshop aims at fostering discussion on the newest privacy trends in embedded systems. Submitted papers should address cutting-edge privacy issues and solutions in the application fields of embedded computing.

Topics of interest include:

• Scalable, robust, and privacy enhancing Embedded Computing.

• Privacy challenges of interoperable and usable Embedded Computing.

• Measurement of Embedded Computing privacy leakage.

• Privacy frameworks for Embedded Computing.

• Threat models and attack strategies for privacy in Embedded Computing.

• Data integrity in Embedded Computing.

• Identity and access management in Embedded Computing.

• Privacy enhancing and anonymization techniques in Embedded Computing.

• Trust management in Embedded Computing.

• Testbeds, and experimental results.

• Blockchain-based identity management and access control systems.

• Differential privacy techniques in Embedded Computing.

• k-anonymity techniques in Embedded Computing.

• Data encryption in Embedded Computing.

• Privacy-enhancing technologies.

• Personal Data Governance.

• Data protection in Embedded Computing.

• Cybersecurity and data protection measures.

• Data protection best practices across verticals

• GDPR compliance in Embedded Computing

The Call for Paper in PDF format will soon be available.