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检索条件"任意字段=Conference on Internet Performance and Control of Network Systems II"

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internet of Things-Based Air Pollution Monitoring System for the Indoor Environment Utilizing Light Fidelity Technology 9

Internet of Things-Based Air Pollution Monitoring System for...

引用

9th International conference on Optimization and Applications, ICOA 2023

作者： Alnajjar, Satea Hikmat Mahmoud, Haneen Mohammed AL-iraqia University Department of Network Engineering Baghdad Iraq AL-iraqia University Department of Computer Engineering Baghdad Iraq

ISBN: (纸本)9798350312546

Indoor air pollution is a major environmental health problem. Exposure to air pollutants can cause many negative health effects, including respiratory problems and heart diseases. To control indoor air pollution, continuous monitoring is necessary. This paper presents an air pollution monitoring system based on the internet of Things (IoT), which refers to the network of physical objects embedded with sensors, software, and connectivity to enable them to exchange data with other connected devices and systems over the communication network. It is suggested to use optical wireless communication (OWC) via light fidelity (Li-Fi) that utilizes visible LED lighting for data transmission purposes. Visible light communication (VLC) was selected due to the current congestion of the radio frequency band, which is extensively employed for data transmission and unable to satisfy the requirements of the forthcoming 6th generation networks. In this paper, the air pollution monitoring system consists of a MQ135 sensor and a dust module sensor to measure polluted data in an indoor environment;the sensors are connected to the Arduino microcontroller for digital processing;and the measured data are transmitted to the ThingSpeak cloud by utilizing an ESP-32 module. The user can access the ThingSpeak web application to monitor air pollution levels through the VLC system. Optisystem tool V18 simulates the VLC system connected with fiber optic channel (FOC) and free-space optic (FSO) channels to transmit the link of the web application to the end user. This paper intends to verify the performance of the VLC system. The proposed system's performance was evaluated based on the quality factor and the bit error rate (BER) at varying distances in dusty weather. The proposed system demonstrated a satisfactory performance up to an estimated distance of 1300 m in dusty conditions. Despite the challenging environmental conditions encountered by the transmission network, VLC has shown its capabili

关键词： internet of things

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Detection and mitigation of deception attacks on cloud-based industrial control systems 25

Detection and mitigation of deception attacks on cloud-based...

引用

25th conference on Innovation in Clouds, internet and networks (ICIN)

作者： Akbarian, Fatemeh Tarneberg, William Fitzgerald, Emma Kihl, Maria Lund Univ Dept Elect & Informat Technol Lund Sweden

ISBN: (纸本)9781728186887

In recent years, because the cloud can provide huge advantages regarding storage and computing resources, industry has been motivated to move industrial control systems to the cloud. However, the cloud also introduces major security challenges, since moving control systems to the cloud can enable attackers to infiltrate the system and establish an attack that can lead to damages and disruptions with potentially catastrophic consequences. Therefore, intrusion detection and mitigation mechanisms are crucial for cloud-based industrial control systems. In this paper, we propose a method for detection and mitigation of deception attacks on actuator signals in cloud-based industrial control systems. We validate our solution on a real testbed and evaluate its capability by subjecting it to a set of attacks. Our proposed solution can detect the attack in a timely manner and keep the plant stable, with an acceptable performance during the attack.

关键词： Cloud control systems Deception attack Attack detection Attack mitigation

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Smart Security: A Biometric Access control and Tracking Architecture for iioT Environments 2024

Smart Security: A Biometric Access Control and Tracking Arch...

引用

12th Euro-American conference on Telematics and Information systems, EATIS 2024

作者： Filho, Aneil De Souza De Lima, Brendon Carvalho, Celso Barbosa Paz, Diogenes Yasuda, Lucas Mendes, Otoniel Casas, Vitoriano Rocha, Williame Femtolab UEA Brazil DTEC FT PPGEE UFAM Brazil

ISBN: (纸本)9798400717338

This article introduces Smart Security, an architecture for access control and biometric tracking in the context of the Industrial internet of Things (iioT), a field that becomes increasingly important as industry 4.0 evolves. Our proposal is unique integrating RFID, multimodal biometric authentication, and personnel monitoring, significantly strengthening the security infrastructure in industrial environments. In a scenario where security threats are increasingly sophisticated and manufacturing environments require greater operational efficiency, we highlight how IoT can be a fundamental ally both in enhancing security and in optimizing processes. The main contributions of this work include: i) the enhancement of security and asset traceability, using RFID tags on mother POS (Point of Sale) equipment;ii) multimodal and multifactorial biometric access control in secure rooms;iii) personnel monitoring through facial recognition, even in situations of facial obstruction;iv) and an integrated system that simplifies security operations, promoting a safer and more efficient environment. In addition to describing the implementation of the Smart Security proposal, the article assesses the CPU and GPU processing performance of the people counting subsystem, offering future perspectives on the evolution of our proposal. This work not only responds to the growing demands for more robust security in industrial contexts but also paves the way for new integrated approaches that can transform security management in iioT environments. © 2024 ACM.

关键词： Access control

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Decentralized AI for Edge Devices with Federated Learning in the internet of Things

Decentralized AI for Edge Devices with Federated Learning in...

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2023 International conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Gouri, M.S. Nagarajan, M. Hussain, Mohammed Waheeduddin Jayachitra, T. Jothikumar, R. Sathya, S. Baselios Mathews II College of Engineering Lake View Muthupilakadu Department of Computer Science and Engineering Kollam Kerala Sasthamcotta India Bharath Institute of Higher Education and Research Department of Electronics and Communication Engineering Chennai India Shadan College of Engineering and Technology Department of Information Technology Peerancheru Hyderabad India Sharda University School of Engineering and Technology Department of Electrical Electronics and Communication Engineering Uttar Pradesh Greater Noida India Shadan College of Engineering and Technology Department of Computer Science and Engineering Peerancheru Hyderabad India GRT Institute of Engineering and Technology Department of Computer Science and Engineering Tiruttani India

ISBN: (纸本)9798350319200

As a result of the development of the internet of Things (IoT), connectivity and applications that are driven by data have entered a new age. Decentralised artificial intelligence with federated learning has evolved as a game-changing concept in this environment, giving answers to urgent challenges like as data privacy, network latency, and resource optimisation. This ecosystem is characterised by constant change. In this research project, we investigate the fundamentals of decentralised artificial intelligence and its consequences for edge devices in IoT networks. The research presented in this paper demonstrates, via a series of tests, that it is possible to strike an appropriate balance between data privacy and model performance by combining decentralised AI with federated learning. The research results provide system designers with helpful information by drawing attention to the trade-offs that exist between the number of devices, the number of communication cycles, and the level of privacy that is afforded. With the help of decentralised artificial intelligence, businesses are able to take advantage of the opportunities presented by the internet of Things (IoT) without sacrificing the confidentiality of their data or the responsiveness of their real-time applications. This paper provides a cornerstone reference, setting the way for further research that may improve privacy approaches, expand to larger IoT networks, and identify fresh uses for decentralised AI in the dynamic environment of the internet of Things (IoT). © 2023 IEEE.

关键词： Decentralized AI Experimental Results Federated Learning internet of Things (IoT) IoT Ecosystem Latency Reduction network Efficiency Privacy-Preserving Mechanisms Standardized Protocols

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Detection of network Attacks on Application Servers Using Deep Learning in IoT Environments 5

Detection of Network Attacks on Application Servers Using De...

引用

5th International conference on Advancements in Computing, ICAC 2023

作者： Meegammana, Niranjan W. Fernando, Harinda Shilpa Sayura Foundation Cyber Security Research Lab Kandy Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798350358131

internet of Things (IoT) comprises interconnected smart devices that collect data, control systems, are increasingly used in critical infrastructure, and raise security concerns due to their inherent vulnerabilities, where conventional security measures struggle to defend IoT networks. This research explores the use of Deep Learning for detecting network attacks on IoT application servers, addressing vital security concerns. The study, employing the Artificial Neural network (ANN) DL model, achieved an impressive 93% accuracy and precision Score of 0.99, highlighting its robustness in identifying various network attack types on IoT application servers. Furthermore, it demonstrated strong performance in terms of precision, recall, and F1 scores, around 0.95, 0.92, and 0.93, respectively, showcasing the ANN model's ability to make precise predictions while minimizing false positives. These findings indicate that DL, especially the ANN model, significantly strengthens IoT security by safeguarding application servers from diverse security threats. Future work will focus on countering emerging zero-day attacks and further integrating the ANN model with application firewalls to enhance IoT security. © 2023 IEEE.

关键词： internet of things

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TaDA: Task Decoupling Architecture for the Battery-less internet of Things 24

TaDA: Task Decoupling Architecture for the Battery-less Inte...

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22nd ACM conference on Embedded networked Sensor systems, SenSys 2024

作者： Song, Weining Kaxiras, Stefanos Voigt, Thiemo Yao, Yuan Mottola, Luca Uppsala University Uppsala Sweden Uppsala University RISE Sweden Politecnico di Milano Milan Italy RISE Uppsala Universit Sweden

ISBN: (纸本)9798400706974

We present TaDA, a system architecture enabling efficient execution of internet of Things (IoT) applications across multiple computing units, powered by ambient energy harvesting. Low-power microcontroller units (MCUs) are increasingly specialized;for example, custom designs feature hardware acceleration of neural network inference, next to designs providing energy-efficient input/output. As application requirements are growingly diverse, we argue that no single MCU can efficiently fulfill them. TaDA allows programmers to assign the execution of different slices of the application logic to the most efficient MCU for the job. We achieve this by decoupling task executions in time and space, using a special-purpose hardware interconnect we design, while providing persistent storage to cross periods of energy unavailability. We compare our prototype performance against the single most efficient computing unit for a given workload. We show that our prototype saves up to 96.7% energy per application round. Given the same energy budget, this yields up to a 68.7x throughput improvement. © 2024 Copyright is held by the owner/author(s).

关键词： Budget control

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Robust Intrusion Detection for Resilience Enhancement of Industrial control systems: An Extended State Observer Approach

Robust Intrusion Detection for Resilience Enhancement of Ind...

引用

IEEE Texas Power and Energy conference (TPEC)

作者： Ahmad, Saif Ahmed, Hafiz INP ENSEEIHT Lab Plasma & Convers Energie F-31071 Toulouse France Univ Sheffield Nucl AMRC Midlands Derby DE73 5SS England

ISBN: (纸本)9781665479035

We address the problem of attack signal estimation in industrial control systems that are subjected to actuator false data injection attack (FDIA) and where the sensor measurements are corrupted by non-negligible high-frequency measurement noise. The actuator FDIA signal is categorized as disturbance to be estimated and subsequently compensated, based on the concept of extended state observer (ESO). We investigate the efficacy of two alternatives to conventional ESO namely, cascade ESO (CESO) and low-power higher-order ESO (LHESO), that guarantee improved estimation performance in case of noisy measurement data as well as time-varying attack signals. Simulation and experimental results under different types of FDIAs demonstrate the advantages of designed schemes in comparison to conventional linear and nonlinear ESOs, using network motion control system as an illustrative example. The results highlight the limitations of conventional ESO under noisy measurement data, particularly nonlinear ESO which is based on fal(center dot) function and commonly used in control literature.

关键词： Actuator false data injection attack extended state observer industrial control system measurement noise

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Study on Active Defense of Honeypot-Based Industrial control network 23

Study on Active Defense of Honeypot-Based Industrial Control...

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23rd IEEE International conference on High performance Computing and Communications, 7th IEEE International conference on Data Science and systems, 19th IEEE International conference on Smart City and 7th IEEE International conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Wei, Xunsi Yang, Dequan Beijing Institute of Technology School of Computer Beijing100081 China Network Information Technology Center Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781665494571

With the rapid development of information, network security and information have played an increasingly important role in national production. As a result, the environment and application of industrial control networks are under more and more network security threats. Furthermore, most applications of industrial control networks belong to critical infrastructure, so to guarantee the security of industrial control networks has become more significant, and the defense of it is one of the essential issues in need of being solved. This paper focuses on studying the active protection for the security of industrial control networks and discusses the role of honeypot in the network security for the defense strategy of the industrial control network. Firstly, this paper introduces the theoretical knowledge of honeypots. Secondly, it analyzes the existing problems and development prospects of the honeypot. And finally, under the background of the industrial control network, it designs the SSH honeypot based on Transmission control Protocol/internet Protocol (TCP/TP), which is divided into two modules, including SSH information collection and alarm. This system can deploy based on the Docker of Linux. Through simulation practice, it proves that honeypot can effectively capture the attackers' attack and make an early warning to improve network security. © 2021 IEEE.

关键词： Industrial control Linux TCPIP Production network security Critical infrastructure

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Blockchain-based Authentication Scheme for Vehicle network Nodes 3

Blockchain-based Authentication Scheme for Vehicle Network N...

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3rd International conference on Blockchain Technology and Information Security, ICBCTIS 2023

作者： Di, Xiaoqiang Sun, Yitong Lu, Junchu Dai, Weiyi Qi, Hui Changchun University of Science and Technology Jilin Province Changchun China

ISBN: (纸本)9798350340402

internet of Vehicles (IoV) has developed into a useful service platform between vehicles and other vehicles, vehicles and roadways, and vehicles and pedestrians as a result of advancements in communication technology. However, along with the intelligent and networked IoV, IoV security issues are increasingly emerging, which often lead to extremely serious consequences. For example, when a vehicle is remotely attacked and maliciously controlled, it can lead to user privacy leakage. Attackers can also control the driving of vehicles through attacks, and there may even be a large number of connected cars being controlled in bulk, ultimately causing major social security incidents. In the internet of Vehicles, authentication technology is one of the main solutions to address the security issues of the internet of Vehicles. Many researchers have conducted some research on the authentication technology of vehicular network, but the traditional authentication scheme under the centralized system has problems such as frequent single-point failures and high overhead. When blockchain technology is properly implemented to the vehicle network environment, its security outperforms that of centralized systems due to features like decentralization, tamper-proof, security, and traceability. Because of this, we construct an optimization technique based on the Practical Byzantine Fault Tolerance (PBFT) algorithm in this work and present an efficient IoV decentralized authentication scheme based on the consensus algorithm of blockchain technology. After performance analysis, it is proved that our scheme has better performance and higher security. © 2023 IEEE.

关键词： Blockchain

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Adaptive Discrete-Time Sliding Mode control Design for Buck Converters with Disturbances 42

Adaptive Discrete-Time Sliding Mode Control Design for Buck ...

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42nd Chinese control conference, CCC 2023

作者： Liu, Peng Wang, Zuo School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Industrial Internet of Things & Network Control Chongqing400065 China Shenzhen Research Institute Southeast University Shenzhen518063 China

ISBN: (纸本)9789887581543

In this paper, an adaptive discrete-time sliding mode controller (ADSMC) is investigated for buck converter systems with multiple external disturbances and parameter uncertainties. To improve the tracking accuracy and reduce the range of the quasi-sliding mode domain (QSMD), the second-order difference of disturbance estimations are introduced into the controller, which are provided by a discrete disturbance observer. Furthermore, an adaptive reaching law is implemented instead of constant gain to alleviate the control input chattering. Both dynamic and steady-state performance analyses are presented. Finally, simulation results are illustrated to demonstrate the control performance. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： controllers

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