Envisioning Tool Support for Designing Privacy-Aware Internet of Thing Applications

TL;DR

This paper advocates for a new tool to assist in designing privacy-aware IoT applications, addressing current gaps in privacy considerations during IoT development.

Contribution

It proposes a research vision for a privacy-aware IoT design tool that transforms, validates, and verifies privacy considerations in IoT applications.

Findings

Identifies the need for privacy-aware design tools in IoT development.

Outlines core functionalities and practical use of the proposed tool.

Highlights potential benefits for privacy education and compliance.

Abstract

The design and development process for Internet of Things (IoT) applications is more complicated than for desktop, mobile, or web applications. IoT applications require both software and hardware to work together across multiple different types of nodes (e.g., microcontrollers, system-on-chips, mobile phones, miniaturised single-board computers, and cloud platforms) with different capabilities under different conditions. IoT applications typically collect and analyse personal data that can be used to derive sensitive information about individuals. Without proper privacy protections in place, IoT applications could lead to serious privacy violations. Thus far, privacy concerns have not been explicitly considered in software engineering processes when designing and developing IoT applications, partly due to a lack of tools, technologies, and guidance. This paper presents a research vision that argues the importance of developing a privacy-aware IoT application design tool to address the challenges mentioned above. This tool should not only transform IoT application designs into privacy-aware application designs but also validate and verify them. First, we outline how this proposed tool should work in practice and its core functionalities. Then, we identify research challenges and potential directions towards developing the proposed tool. We anticipate that this proposed tool will save many engineering hours which engineers would otherwise need to spend on developing privacy expertise and applying it. We also highlight the usefulness of this tool towards privacy education and privacy compliance.