skip to main content

Title: Design patterns for the industrial Internet of Things
The Internet of Things (IoT) is a vast collection of interconnected sensors, devices, and services that share data and information over the Internet with the objective of leveraging multiple information sources to optimize related systems. The technologies associated with the IoT have significantly improved the quality of many existing applications by reducing costs, improving functionality, increasing access to resources, and enhancing automation. The adoption of IoT by industries has led to the next industrial revolution: Industry 4.0. The rise of the Industrial IoT (IIoT) promises to enhance factory management, process optimization, worker safety, and more. However, the rollout of the IIoT is not without significant issues, and many of these act as major barriers that prevent fully achieving the vision of Industry 4.0. One major area of concern is the security and privacy of the massive datasets that are captured and stored, which may leak information about intellectual property, trade secrets, and other competitive knowledge. As a way forward toward solving security and privacy concerns, we aim in this paper to identify common input-output (I/O) design patterns that exist in applications of the IIoT. These design patterns enable constructing an abstract model representation of data flow semantics used by such applications, and therefore better understand how to secure the information related to IIoT operations. In this paper, we describe communication protocols and identify common I/O design patterns for IIoT applications with an emphasis on data flow in edge devices, which, in the industrial control system (ICS) setting, are most often involved in process control or monitoring.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
2018 14th IEEE International Workshop on Factory Communication Systems (WFCS)
Page Range / eLocation ID:
1 to 10
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    Internet of Things (IoT) devices are becoming increasingly popular and offer a wide range of services and functionality to their users. However, there are significant privacy and security risks associated with these devices. IoT devices can infringe users' privacy by ex-filtrating their private information to third parties, often without their knowledge. In this work we investigate the possibility to identify IoT devices and their location in an Internet Service Provider's network. By analyzing data from a large Internet Service Provider (ISP), we show that it is possible to recognize specific IoT devices, their vendors, and sometimes even their specific model, and to infer their location in the network. This is possible even with sparsely sampled flow data that are often the only datasets readily available at an ISP. We evaluate our proposed methodology to infer IoT devices at subscriber lines of a large ISP. Given ground truth information on IoT devices location and models, we were able to detect more than 77% of the studied IoT devices from sampled flow data in the wild. 
    more » « less
  2. Industrial Internet of Things (IIoT) has been shown to be of great value to the deployment of smart industrial environment. With the immense growth of IoT devices, dynamic spectrum sharing is introduced, envisaged as a promising solution to the spectrum shortage in IIoT. Meanwhile, cyber-physical safety issue remains to be a great concern for the reliable operation of IIoT system. In this paper, we consider the dynamic spectrum access in IIoT under a Received Signal Strength (RSS) based adversarial localization attack. We employ a practical and effective power perturbation approach to mitigate the localization threat on the IoT devices and cast the privacy-preserving spectrum sharing problem as a stochastic channel selection game. To address the randomness induced by the power perturbation approach, we develop a two-timescale distributed learning algorithm that converges almost surely to the set of correlated equilibria of the game. The numerical results show the convergence of the algorithm and corroborate that the design of two-timescale learning process effectively alleviates the network throughput degradation brought by the power perturbation procedure. 
    more » « less
  3. Internet of Things (IoT) is becoming increasingly popular due to its ability to connect machines and enable an ecosystem for new applications and use cases. One such use case is industrial loT (1IoT) that refers to the application of loT in industrial settings especially engaging instrumentation and control of sensors and machines with Cloud technologies. Industries are counting on the fifth generation (5G) of mobile communications to provide seamless, ubiquitous and flexible connectivity among machines, people and sensors. The open radio access network (O-RAN) architecture adds additional interfaces and RAN intelligent controllers that can be leveraged to meet the IIoT service requirements. In this paper, we examine the connectivity requirements for IIoT that are dominated by two industrial applications: control and monitoring. We present the strength, weakness, opportunity, and threat (SWOT) analysis of O-RAN for IIoT and provide a use case example which illustrates how O-RAN can support diverse and changing IIoT network services. We conclude that the flexibility of the O-RAN architecture, which supports the latest cellular network standards and services, provides a path forward for next generation IIoT network design, deployment, customization, and maintenance. It offers more control but still lacks products-hardware and software-that are exhaustively tested in production like environments. 
    more » « less
  4. Consumer Internet of Things (IoT) devices are increasingly common, from smart speakers to security cameras, in homes. Along with their benefits come potential privacy and security threats. To limit these threats a number of commercial services have become available (IoT safeguards). The safeguards claim to provide protection against IoT privacy risks and security threats. However, the effectiveness and the associated privacy risks of these safeguards remains a key open question. In this paper, we investigate the threat detection capabilities of IoT safeguards for the first time. We develop and release an approach for automated safeguards experimentation to reveal their response to common security threats and privacy risks. We perform thousands of automated experiments using popular commercial IoT safeguards when deployed in a large IoT testbed. Our results indicate not only that these devices may be ineffective in preventing risks, but also their cloud interactions and data collection operations may introduce privacy risks for the households that adopt them. 
    more » « less
  5. null (Ed.)
    Industrial Internet of Things (IIoT) systems aim to interconnect a large number of heterogeneous industrial sensing and actuation devices through both wired and wireless communication technologies and further connect them to the Internet to achieve ubiquitous sensing, computing and control services [1]. As a representative IIoT technology, 6TiSCH [2] targets at gluing together the 802.15.4e data link layer (offering industrial performance in terms of timing, reliability and power consumption) and an IP-enabled upper layer stack to achieve both deterministic network performance and seamless integration with Internet services. In recent years, 6TiSCH has been receiving increasing attentions from both industry and academia. We have witnessed its wide deployment in many industrial domains, including advanced manufacturing, industrial process control, smart grids, and healthcare. 
    more » « less