scholarly journals Low Computational Sensing with Goertzel Filtering for Mobile Industrial IoT Devices

2020 ◽  
Author(s):  
Jaswinder Lota ◽  
Andreas Demosthenous
Keyword(s):  
Computational Sensing ◽  
Industrial Iot ◽  
Iot Devices

A Smart Monitoring Industrial IOT Devices from Outsider Threats

2021 ◽  
pp. 913-923
Author(s):  
T. Anandhi ◽  
D. Radha Krishna ◽  
Koushik Pilli ◽  
P. Ajitha ◽  
A. Sivasangari ◽  
...  
Keyword(s):  
Industrial Iot ◽  
Iot Devices

scholarly journals Security-Aware Data Offloading and Resource Allocation For MEC Systems: A Deep Reinforcement Learning

2021 ◽  
Author(s):  
Ibrahim Elgendy ◽  
Ammar Muthanna ◽  
Mohammad Hammoudeh ◽  
Hadil Ahmed Shaiba ◽  
Devrim Unal ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Large Scale ◽  
Optimal Solution ◽  
Security Requirements ◽  
Optimization Approach ◽  
Shared Resources ◽  
Data Offloading ◽  
Daily Lives ◽  
Industrial Iot ◽  
Iot Devices

The Internet of Things (IoT) is permeating our daily lives where it can provide data collection tools and important measurement to inform our decisions. In addition, they are continually generating massive amounts of data and exchanging essential messages over networks for further analysis. The promise of low communication latency, security enhancement and the efficient utilization of bandwidth leads to the new shift change from Mobile Cloud Computing (MCC) towards Mobile Edge Computing (MEC). In this study, we propose an advanced deep reinforcement resource allocation and securityaware data offloading model that considers the computation and radio resources of industrial IoT devices to guarantee that shared resources between multiple users are utilized in an efficient way. This model is formulated as an optimization problem with the goal of decreasing the consumption of energy and computation delay. This type of problem is NP-hard, due to the curseof-dimensionality challenge, thus, a deep learning optimization approach is presented to find an optimal solution. Additionally, an AES-based cryptographic approach is implemented as a security layer to satisfy data security requirements. Experimental evaluation results show that the proposed model can reduce offloading overhead by up to 13.2% and 64.7% in comparison with full offloading and local execution while scaling well for large-scale devices.

scholarly journals Model-driven development of asynchronous message-driven architectures with AsyncAPI

2021 ◽  
Author(s):  
Abel Gómez ◽  
Markel Iglesias-Urkia ◽  
Lorea Belategi ◽  
Xabier Mendialdua ◽  
Jordi Cabot
Keyword(s):  
Cyber Physical Systems ◽  
Complex Data ◽  
Previous Knowledge ◽  
Physical Systems ◽  
Everyday Objects ◽  
Model Driven ◽  
Design And Implementation ◽  
Industrial Iot ◽  
Iot Devices ◽  
The Internet Of Things

AbstractIn the Internet-of-Things (IoT) vision, everyday objects evolve into cyber-physical systems. The massive use and deployment of these systems has given place to the Industry 4.0 or Industrial IoT (IIoT). Due to its scalability requirements, IIoT architectures are typically distributed and asynchronous. In this scenario, one of the most widely used paradigms is publish/subscribe, where messages are sent and received based on a set of categories or topics. However, these architectures face interoperability challenges. Consistency in message categories and structure is the key to avoid potential losses of information. Ensuring this consistency requires complex data processing logic both on the publisher and the subscriber sides. In this paper, we present our proposal relying on AsyncAPI to automate the design and implementation of these asynchronous architectures using model-driven techniques for the generation of (part of) message-driven infrastructures. Our proposal offers two different ways of designing the architectures: either graphically, by modeling and annotating the messages that are sent among the different IoT devices, or textually, by implementing an editor compliant with the AsyncAPI specification. We have evaluated our proposal by conducting a set of experiments with 25 subjects with different expertise and background. The experiments show that one-third of the subjects were able to design and implement a working architecture in less than an hour without previous knowledge of our proposal, and an additional one-third estimated that they would only need less than two hours in total.

scholarly journals An AAA solution for securing industrial IoT devices using next generation access control

2018 ◽  
Author(s):  
Katyayani Kiranmayee Kolluru ◽  
Cristina Paniagua ◽  
Jan van Deventer ◽  
Jens Eliasson ◽  
Jerker Delsing ◽  
...  
Keyword(s):  
Access Control ◽  
Next Generation ◽  
Industrial Iot ◽  
Iot Devices

Cyber-Physical System and Internet of Things Security

2021 ◽  
pp. 328-357
Author(s):  
Thomas Ulz ◽  
Sarah Haas ◽  
Christian Steger
Keyword(s):  
Internet Of Things ◽  
Public Awareness ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Industrial Iot ◽  
Confidential Data ◽  
Iot Devices ◽  
The Internet Of Things

An increase of distributed denial-of-service (DDoS) attacks launched by botnets such as Mirai has raised public awareness regarding potential security weaknesses in the Internet of Things (IoT). Devices are an attractive target for attackers because of their large number and due to most devices being online 24/7. In addition, many traditional security mechanisms are not applicable for resource constraint IoT devices. The importance of security for cyber-physical systems (CPS) is even higher, as most systems process confidential data or control a physical process that could be harmed by attackers. While industrial IoT is a hot topic in research, not much focus is put on ensuring information security. Therefore, this paper intends to give an overview of current research regarding the security of data in industrial CPS. In contrast to other surveys, this work will provide an overview of the big CPS security picture and not focus on special aspects.

Decades of Internet of Things towards 21st Century: A Research-Based Introspective

2021 ◽  
Author(s):  
NAGAJAYANTHI BOOBALAKRISHNAN
Keyword(s):  
Internet Of Things ◽  
Cyber Attacks ◽  
Embedded Internet ◽  
Industrial Iot ◽  
Voice User ◽  
Block Chain ◽  
Iot Devices ◽  
Data Ecosystem ◽  
The Internet Of Things ◽  
Exchange Data

Abstract Internet connects people to people, people to machine, and machine to machine for a life of serendipity through a Cloud. Internet of Things networks objects or people and integrates them with software to collect and exchange data. The Internet of things (IoT) influences our lives based on how we ruminate, respond, and anticipate. IoT 2020 heralds from the fringes to the data ecosystem and panaches a comfort zone. IoT is overwhelmingly embraced by businessmen and consumers due to increased productivity and convenience. Internet of Things facilitates intelligent device control with cloud vendors like Amazon and Google using artificial intelligence for data analytics, and with digital assistants like Alexa and Siri providing a voice user interface. Smart IoT is all about duplex connecting, processing, and implementing. With 5G, lightning faster rate of streaming analytics is realistic. An amalgamation of technologies has led to this techno-industrial IoT revolution. Centralized IoT architecture is vulnerable to cyber-attacks. With Block Chain, it is possible to maintain transparency and security of the transaction's data. Standardization of IoT devices is achievable with limited vendors based on Platform, Connectivity, and Application. Robotic Process Automation (RPA) using bots has automated laborious tasks in 2019. Embedded Internet using Facial Recognition could reduce the pandemic crisis. Security concerns are addressed with micro-segmentation approaches. IoT, an incredible vision of the future makes systems adaptive with customized features, responsive with increased efficiency, and procurable with optimized cost. This paper delivers a comprehensive insight into the technical perspectives of IoT, focusing on interoperability, flexibility, scalability, mobility, security, transparency, standardization, and low energy.

scholarly journals Whisper: Programmable and Flexible Control on Industrial IoT Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4048 ◽  
Author(s):  
Esteban Municio ◽  
Johann Marquez-Barja ◽  
Steven Latré ◽  
Stefano Vissicchio
Keyword(s):  
Low Power ◽  
Network Control ◽  
Lossy Networks ◽  
Jamming Attacks ◽  
Network Nodes ◽  
Flexible Control ◽  
Routing And Scheduling ◽  
Industrial Iot ◽  
Iot Devices ◽  
And Coping

Software Defined Networking (SDN) centralizes network control to improve network programmability and flexibility. Contrary to wired settings, it is unclear how to support SDN in low power and lossy networks like typical Internet of Things (IoT) ones. Challenges encompass providing reliable in-band connectivity between the centralized controller and out-of-range nodes, and coping with physical limitations of the highly resource-constrained IoT devices. In this work, we present Whisper, an enabler for SDN in low power and lossy networks. The centralized Whisper controller of a network remotely controls nodes’ forwarding and cell allocation. To do so, the controller sends carefully computed routing and scheduling messages that are fully compatible with the protocols run in the network. This mechanism ensures the best possible in-band connectivity between the controller and all network nodes, capitalizing on an interface which is already supported by network devices. Whisper’s internal algorithms further reduce the number of messages sent by the controller, to make the exerted control as lightweight as possible for the devices. Beyond detailing Whisper’s design, we discuss compelling use cases that Whisper unlocks, including rerouting around low-battery devices and providing runtime defense to jamming attacks. We also describe how to implement Whisper in current IoT open standards (RPL and 6TiSCH) without modifying IoT devices’ firmware. This shows that Whisper can implement an SDN-like control for distributed low power networks with no specific support for SDN, from legacy to next generation IoT devices. Our testbed experiments show that Whisper successfully controls the network in both the scheduling and routing plane, with significantly less overhead than other SDN-IoT solutions, no additional latency and no packet loss.

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