Security and Machine Learning Adoption in IoT: A Preliminary Study of IoT Developer Discussions

TL;DR

This study analyzes IoT developer discussions on Stack Overflow, revealing insights into security concerns and ML adoption challenges, which can guide future improvements in IoT security and machine learning integration.

Contribution

It provides the first focused analysis of IoT developer discussions on Stack Overflow regarding security and machine learning, highlighting key challenges and interests.

Findings

12% of sentences discuss security issues

0.12% of sentences discuss ML-related topics

Developers seek secure data sharing methods and face challenges integrating ML into resource-constrained IoT devices

Abstract

Internet of Things (IoT) is defined as the connection between places and physical objects (i.e., things) over the internet/network via smart computing devices. Traditionally, we learn about the IoT ecosystem/problems by conducting surveys of IoT developers/practitioners. Another way to learn is by analyzing IoT developer discussions in popular online developer forums like Stack Overflow (SO). However, we are aware of no such studies that focused on IoT developers' security and ML-related discussions in SO. This paper offers the results of preliminary study of IoT developer discussions in SO. We find around 12% of sentences contain security discussions, while around 0.12% sentences contain ML- related discussions. We find that IoT developers discussing security issues frequently inquired about how the shared data can be stored, shared, and transferred securely across IoT devices and users. We also find that IoT developers are interested to adopt deep neural network-based ML models into their IoT devices, but they find it challenging to accommodate those into their resource-constrained IoT devices. Our findings offer implications for IoT vendors and researchers to develop and design novel techniques for improved security and ML adoption into IoT devices.