Microcontroller Unit Chip Temperature Fingerprint Informed Machine Learning for IIoT Intrusion Detection

Wang, Tingting; Fang, Kai; Wei, Wei; Jing-zhen, Tian; Pan, Yuanyuan; Li, Jianqing

doi:10.1109/tii.2022.3195287

Cited by 18 publications

(3 citation statements)

References 26 publications

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“…In recent years, nanobiosensors have attracted more attention than ever before due to the active development of nanoscience and interface science. Teir development is remarkable and applications are widespread [4].…”

Section: Development Of Nanotechnologymentioning

confidence: 99%

Application of Microcontroller-Based Multipath Servos in Industrial Robot Control Systems

2023

Journal of Robotics

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In recent years, nanotechnology has continued to develop, especially the use of nanomaterials in various fields. Microcontroller is the most typical embedded system at this stage. With the development of science and technology, microcontroller has been widely used in people’s production life. A simple and practical multiservo controller can be built by using microcontroller and LED control chip PCA9685, which can realize at least 16 channels of servo control. In this paper, the control program of multichannel actuator is designed in detail, and the speed regulation of multichannel actuator is studied, which is applied to the industrial robot system driven by actuator. Nanomaterials, as new materials with various unique properties, have great application prospects, and this paper investigates the extension of nanomaterials in the field of robotic systems.

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Section: Development Of Nanotechnologymentioning

confidence: 99%

Application of Microcontroller-Based Multipath Servos in Industrial Robot Control Systems

2023

Journal of Robotics

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“…Trough the long-term use and damage of bridges, certain deformation may occur, which seriously endangers the safety and stability of bridges. Tus, it is of important practical signifcance to improve its deformation measurement and detection [18]. According to the efcient measurement and inspection technology means, the defciencies are found early and then solved scientifcally and reasonably to ensure the bridge safety and reliability reasonably.…”

Section: Deformation Measurement and Monitoring Of Bridgesmentioning

confidence: 99%

Discovery and Discrimination of Bridge Engineering Safety Issues by BIM Virtual Scene Combined with Robotic Mapping

Gui-lin

Shao-wu

Gao

et al. 2023

Journal of Robotics

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All along, safety accidents in the field of bridge construction have continued to arise, costing society's development financial and material resources and taking away people’s personal safety, turning into an urgent need for safety managers in the field to solve the subject research. Researchers look forward to continued innovative exploration to find new ways of working safely and using them in the construction industry. On this basis, BIM virtual scenes are introduced to create a universal scene specification dataset in the field of bridge construction and a dataset of unsafe potential hazard characteristics in the field of bridge construction. Nanobots are artificial intelligence systems built to simulate biological nanomachine constructions in life activities and important biological events in life processes. In this paper, BIM virtual scenarios incorporating intelligent nanomaterial robot mapping technology are migrated to bridge engineering safety management. According to the collected construction scene images and BIM (building information model) virtual scenes, build the construction scene dataset, use intelligent robots to obtain construction scenes, and load them into the trained construction on-the-spot neural network modeling to complete the bridge construction scene identification safety discrimination to select more comprehensive and more stringent management solutions as safety management personnel management methods on-the-spot.

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“…The SEI publications surveyed under this section focused on the environmental temperature impacts on SEI and not emitterconnected operating temperature(s). The former is not new to the SEI community [135] but has not received much attention [114,136,137]. The latter is addressed in Section 10.5 of this survey.…”

Section: Operating Temperature Conditionsmentioning

confidence: 98%

Considerations, Advances, and Challenges Associated with the Use of Specific Emitter Identification in the Security of Internet of Things Deployments: A Survey

Tyler,

Fadul,

Reising

2023

Information

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Initially introduced almost thirty years ago for the express purpose of providing electronic warfare systems the capabilities to detect, characterize, and identify radar emitters, Specific Emitter Identification (SEI) has recently received a lot of attention within the research community as a physical layer technique for securing Internet of Things (IoT) deployments. This attention is largely due to SEI’s demonstrated success in passively and uniquely identifying wireless emitters using traditional machine learning and the success of Deep Learning (DL) within the natural language processing and computer vision areas. SEI exploits distinct and unintentional features present within an emitter’s transmitted signals. These distinctive and unintentional features are attributed to slight manufacturing and assembly variations within and between the components, sub-systems, and systems comprising an emitter’s Radio Frequency (RF) front end. Although sufficient to facilitate SEI, these features do not hinder normal operations such as detection, channel estimation, timing, and demodulation. However, despite the plethora of SEI publications, it has remained largely a focus of academic endeavors, primarily focusing on proof-of-concept demonstration and little to no use in operational networks for various reasons. The focus of this survey is a review of SEI publications from the perspective of its use as a practical, effective, and usable IoT security mechanism; thus, we use IoT requirements and constraints (e.g., wireless standard, nature of their deployment) as a lens through which each reviewed paper is analyzed. Previous surveys have not taken such an approach and have only used IoT as motivation, a setting, or a context. In this survey, we consider operating conditions, SEI threats, SEI at scale, publicly available data sets, and SEI considerations that are dictated by the fact that it is to be employed by IoT devices or IoT infrastructure.

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Microcontroller Unit Chip Temperature Fingerprint Informed Machine Learning for IIoT Intrusion Detection

Cited by 18 publications

References 26 publications

Application of Microcontroller-Based Multipath Servos in Industrial Robot Control Systems

Application of Microcontroller-Based Multipath Servos in Industrial Robot Control Systems

Discovery and Discrimination of Bridge Engineering Safety Issues by BIM Virtual Scene Combined with Robotic Mapping

Considerations, Advances, and Challenges Associated with the Use of Specific Emitter Identification in the Security of Internet of Things Deployments: A Survey

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