In the upcoming large-scale Internet of Things(Io T),it is increasingly challenging to defend against malicious traffic,due to the heterogeneity of Io T devices and the diversity of Io T communication protocols.In thi...In the upcoming large-scale Internet of Things(Io T),it is increasingly challenging to defend against malicious traffic,due to the heterogeneity of Io T devices and the diversity of Io T communication protocols.In this paper,we propose a semi-supervised learning-based approach to detect malicious traffic at the access side.It overcomes the resource-bottleneck problem of traditional malicious traffic defenders which are deployed at the victim side,and also is free of labeled traffic data in model training.Specifically,we design a coarse-grained behavior model of Io T devices by self-supervised learning with unlabeled traffic data.Then,we fine-tune this model to improve its accuracy in malicious traffic detection by adopting a transfer learning method using a small amount of labeled data.Experimental results show that our method can achieve the accuracy of 99.52%and the F1-score of 99.52%with only 1%of the labeled training data based on the CICDDoS2019 dataset.Moreover,our method outperforms the stateof-the-art supervised learning-based methods in terms of accuracy,precision,recall and F1-score with 1%of the training data.展开更多
As communication technology and smart manufacturing have developed, the industrial internet of things(IIo T)has gained considerable attention from academia and industry.Wireless sensor networks(WSNs) have many advanta...As communication technology and smart manufacturing have developed, the industrial internet of things(IIo T)has gained considerable attention from academia and industry.Wireless sensor networks(WSNs) have many advantages with broad applications in many areas including environmental monitoring, which makes it a very important part of IIo T. However,energy depletion and hardware malfunctions can lead to node failures in WSNs. The industrial environment can also impact the wireless channel transmission, leading to network reliability problems, even with tightly coupled control and data planes in traditional networks, which obviously also enhances network management cost and complexity. In this paper, we introduce a new software defined network(SDN), and modify this network to propose a framework called the improved software defined wireless sensor network(improved SD-WSN). This proposed framework can address the following issues. 1) For a large scale heterogeneous network, it solves the problem of network management and smooth merging of a WSN into IIo T. 2) The network coverage problem is solved which improves the network reliability. 3) The framework addresses node failure due to various problems, particularly related to energy consumption.Therefore, it is necessary to improve the reliability of wireless sensor networks, by developing certain schemes to reduce energy consumption and the delay time of network nodes under IIo T conditions. Experiments have shown that the improved approach significantly reduces the energy consumption of nodes and the delay time, thus improving the reliability of WSN.展开更多
Today, the number of embedded system was applied in the field of automation and control has far exceeded a variety of general-purpose computer. Embedded system is gradually penetrated into all fields of human society,...Today, the number of embedded system was applied in the field of automation and control has far exceeded a variety of general-purpose computer. Embedded system is gradually penetrated into all fields of human society, and ubiquitous embedded applications constitute the 'ubiquitous' computing era. Embedded operating system is the core of the em-bedded system, and it directly affects the performance of the whole system. Our Liaoning Provincial Key Laboratory of Embedded Technology has successfully developed five kinds of device-level embedded operating systems by more than ten years’ efforts, and these systems are Webit 5.0, Worix, μKernel, iDCX 128 and μc/os-II 128. This paper mainly analyses and compares the implementation mechanism and performance of these five kinds of device-level embedded operating systems in detail.展开更多
结合重庆市某改良A^2/O工艺污水处理的工程实例,介绍了物联网技术和自动控制技术在系统中的应用方案及功能组成。使用物联网技术进行污水取样和相关参数测试,明确污水处理系统各功能部分的工作状态,使用三级计算机分散控制系统对污水处...结合重庆市某改良A^2/O工艺污水处理的工程实例,介绍了物联网技术和自动控制技术在系统中的应用方案及功能组成。使用物联网技术进行污水取样和相关参数测试,明确污水处理系统各功能部分的工作状态,使用三级计算机分散控制系统对污水处理过程进行实时信息化管理。运行结果表明,应用融合物联网的自动控制手段后,系统运行稳定性得到提升,数据采集测试频率可稳定维持在15 min/次,出水达标率>90%,耗电量<0.35 k W·h/m^3。展开更多
基金supported in part by the National Key R&D Program of China under Grant 2018YFA0701601part by the National Natural Science Foundation of China(Grant No.U22A2002,61941104,62201605)part by Tsinghua University-China Mobile Communications Group Co.,Ltd.Joint Institute。
文摘In the upcoming large-scale Internet of Things(Io T),it is increasingly challenging to defend against malicious traffic,due to the heterogeneity of Io T devices and the diversity of Io T communication protocols.In this paper,we propose a semi-supervised learning-based approach to detect malicious traffic at the access side.It overcomes the resource-bottleneck problem of traditional malicious traffic defenders which are deployed at the victim side,and also is free of labeled traffic data in model training.Specifically,we design a coarse-grained behavior model of Io T devices by self-supervised learning with unlabeled traffic data.Then,we fine-tune this model to improve its accuracy in malicious traffic detection by adopting a transfer learning method using a small amount of labeled data.Experimental results show that our method can achieve the accuracy of 99.52%and the F1-score of 99.52%with only 1%of the labeled training data based on the CICDDoS2019 dataset.Moreover,our method outperforms the stateof-the-art supervised learning-based methods in terms of accuracy,precision,recall and F1-score with 1%of the training data.
基金supported by the National Natural Science Foundation of China(61571336)the Science and Technology Project of Henan Province in China(172102210081)the Independent Innovation Research Foundation of Wuhan University of Technology(2016-JL-036)
文摘As communication technology and smart manufacturing have developed, the industrial internet of things(IIo T)has gained considerable attention from academia and industry.Wireless sensor networks(WSNs) have many advantages with broad applications in many areas including environmental monitoring, which makes it a very important part of IIo T. However,energy depletion and hardware malfunctions can lead to node failures in WSNs. The industrial environment can also impact the wireless channel transmission, leading to network reliability problems, even with tightly coupled control and data planes in traditional networks, which obviously also enhances network management cost and complexity. In this paper, we introduce a new software defined network(SDN), and modify this network to propose a framework called the improved software defined wireless sensor network(improved SD-WSN). This proposed framework can address the following issues. 1) For a large scale heterogeneous network, it solves the problem of network management and smooth merging of a WSN into IIo T. 2) The network coverage problem is solved which improves the network reliability. 3) The framework addresses node failure due to various problems, particularly related to energy consumption.Therefore, it is necessary to improve the reliability of wireless sensor networks, by developing certain schemes to reduce energy consumption and the delay time of network nodes under IIo T conditions. Experiments have shown that the improved approach significantly reduces the energy consumption of nodes and the delay time, thus improving the reliability of WSN.
文摘Today, the number of embedded system was applied in the field of automation and control has far exceeded a variety of general-purpose computer. Embedded system is gradually penetrated into all fields of human society, and ubiquitous embedded applications constitute the 'ubiquitous' computing era. Embedded operating system is the core of the em-bedded system, and it directly affects the performance of the whole system. Our Liaoning Provincial Key Laboratory of Embedded Technology has successfully developed five kinds of device-level embedded operating systems by more than ten years’ efforts, and these systems are Webit 5.0, Worix, μKernel, iDCX 128 and μc/os-II 128. This paper mainly analyses and compares the implementation mechanism and performance of these five kinds of device-level embedded operating systems in detail.
文摘结合重庆市某改良A^2/O工艺污水处理的工程实例,介绍了物联网技术和自动控制技术在系统中的应用方案及功能组成。使用物联网技术进行污水取样和相关参数测试,明确污水处理系统各功能部分的工作状态,使用三级计算机分散控制系统对污水处理过程进行实时信息化管理。运行结果表明,应用融合物联网的自动控制手段后,系统运行稳定性得到提升,数据采集测试频率可稳定维持在15 min/次,出水达标率>90%,耗电量<0.35 k W·h/m^3。
