Exploring Strategies for Deploying AI Models in Industrial IoT Systems While Considering Privacy Concerns and Compliance with Data Protection Regulations.

EasyChair Preprint 13287

Abstract

This abstract provides a concise summary of the topic "Exploring strategies for deploying AI models in industrial IoT systems while considering privacy concerns and compliance with data protection regulations."

Industrial Internet of Things (IoT) systems hold immense potential for leveraging artificial intelligence (AI) models to optimize operations and enhance efficiency. However, deploying AI in these systems requires careful consideration of privacy concerns and compliance with data protection regulations to ensure the ethical and responsible use of data.

This paper explores various strategies for deploying AI models in industrial IoT systems while addressing privacy concerns and complying with data protection regulations. It begins by highlighting the importance of privacy and the potential consequences of non-compliance with regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

The strategies discussed in the paper encompass different aspects of privacy and compliance. These include data minimization and anonymization techniques to collect and store only necessary data while protecting sensitive information. Secure data transmission and storage mechanisms, such as encryption and secure communication protocols, are explored to safeguard data during transit and storage.

The paper also delves into edge computing and on-device processing as strategies to reduce reliance on transmitting sensitive data to the cloud, thereby enhancing privacy. Additionally, federated learning is examined as a collaborative approach to train AI models without sharing raw data, ensuring decentralized data privacy.

Keyphrases: AI models, Auditing, Compliance, evaluating, industrial IoT systems

@booklet{EasyChair:13287,
  author    = {Ayuns Luz},
  title     = {Exploring Strategies for Deploying AI Models in Industrial IoT Systems While Considering Privacy Concerns and Compliance with Data Protection Regulations.},
  howpublished = {EasyChair Preprint 13287},
  year      = {EasyChair, 2024}}