Secure and Private AI-based Remote Monitoring and Control in Industrial IoT

EasyChair Preprint 13618

Abstract

Secure and private AI-based remote monitoring and control in Industrial Internet of Things (IIoT) is of paramount importance to ensure the integrity and confidentiality of critical industrial systems. This abstract highlights the challenges, solutions, and benefits associated with implementing robust security and privacy measures in IIoT deployments.

The abstract begins by emphasizing the significance of remote monitoring and control in IIoT and the need for secure and private solutions. It acknowledges the vulnerabilities and risks associated with IIoT systems, such as security breaches and privacy concerns.

The abstract then delves into the key aspects of secure and private AI-based remote monitoring and control. It outlines various measures, including encryption and authentication protocols, access control mechanisms, data privacy techniques (such as anonymization and minimization), threat detection and prevention systems, and secure device management practices.

Keyphrases: Access controls, Data Classification, Data Loss Prevention (DLP), Employee Awareness, Encryption, Vendor security

@booklet{EasyChair:13618,
  author    = {Godwin Olaoye and Harold Jonathan},
  title     = {Secure and Private AI-based Remote Monitoring and Control in Industrial IoT},
  howpublished = {EasyChair Preprint 13618},
  year      = {EasyChair, 2024}}