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Network Security Strategy based on Cloud-Edge Collaboration in Electric Power internet of Things 6

Network Security Strategy Based on Cloud-Edge Collaboration ...

引用

6th international conference on Information Communication and signal Processing, ICICSP 2023

作者： Jiang, Jing Xin, Peizhe Wang, Yudong Zhou, Chengzhen State Grid Economic and Technological Research Institute Beijing China

ISBN: (纸本)9798350339994

In recent years, with the application of Multi-access edge computing (MEC) technology in the power internet of Things (PIOT), the power internet of Things has gradually formed a development trend of large connections, wide coverage, real-time, and intelligence. However, the introduction of MEC makes the power internet of Things involve more information transmission and data processing, and how to strengthen the preventive measures for data security and privacy protection is also a key challenge. Aiming at the problem that the edge nodes in the power internet of Things are vulnerable to attacks, this paper proposes a network security strategy for the power internet of Things based on cloud-edge collaboration. This strategy updates their respective trust values in real time through the communication and interaction between nodes, and quickly detects abnormal nodes in the network based on the trust values. At the same time, this paper implements the abnormal node detection smart contract proposed in this paper based on the Hyperledger Fabric blockchain platform. The experimental results show that the designed abnormal node detection smart contract accurately detects the abnormal nodes in the network, and successfully synchronizes the results with all nodes, effectively ensuring the operation security of the power internet of Things. © 2023 IEEE.

关键词： blockchain MEC network security strategy PIoT smart contract

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Hierarchical DNN-based image Segmentation Algorithm Using Texton, Superpixels, and Layer-Adaptive Loss Functions 16

Hierarchical DNN-Based Image Segmentation Algorithm Using Te...

引用

16th international conference on signal-image technology and internet-based systems (SITIS)

作者： Yu, Cheng-Hsuan Ding, Jian-Jiun Natl Taiwan Univ Grad Inst Commun Engn Taipei Taiwan

ISBN: (纸本)9781665464956

image segmentation is critical to object-oriented image processing. Many conventional segmentation algorithms are based on the superpixel, since it integrates the pixels with similar colors and locations in prior and is beneficial for segmentation. Recently, several segmentation algorithms based on deep learning were developed. However, due to the irregular shape and size of superpixels, it is hard to apply the superpixel directly in a leaning-based segmentation algorithm. In this paper, we propose a novel segmentation method that well integrates the techniques of the deep neural network (DNN), the superpixel, adaptive loss functions, and multi-layer feature extraction. First, different from other learning-based algorithm, which applies an image or its bounding boxes as the input, we adopt the mean and the histogram differences of the features of two superpixels as the input of the DNN to determine whether they should be merged. Moreover, to well consider both largescaled and small-scaled features, a hierarchical architecture is adopted. For different layers, the DNN models with different loss functions are applied. A larger penalty for over-merging is applied in the first layer and a larger penalty for oversegmentation is applied in the following layer. Moreover, according to human perception, the features of colors, areas, the gradient at the boundary, and the texton, which is highly related to the texture, are applied. Experiments show that the proposed method outperforms other state-of-the-art image segmentation methods and produces highly accurate segmentation results.

关键词： image segmentation superpixel merging deep learning

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Security of image Using Watermarking Techniques and Visual Cryptography 6

Security of Image Using Watermarking Techniques and Visual C...

引用

6th international conference on Information systems and Computer Networks, ISCON 2023

作者： Srivastava, Lahar Garg, Hitendra GLA University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350346961

Due to rapid growth in technology there is a need to secure multimedia data like audio, video, text etc. available on the internet. In the proposed work, visual cryptography based watermarking techniques are proposed to secure image data. The watermark is inserted followed by visual cryptography where 'n' numbers of shares are created. DCT and IDCT are implemented to insert the watermark. The k shares out of n are required to get the original image where watermark is authenticated. PSNR is used for comparing the original image with images obtained after decryption.. © 2023 IEEE.

关键词： Copyrights

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Computer Network Information Security Supervision and Protection Strategy with internet of Things Information technology 9

Computer Network Information Security Supervision and Protec...

引用

9th international conference on Intelligent Computing and signal Processing, ICSP 2024

作者： Nan, Xiang Parthasarathy, Rajamohan Wang, Chu School of Information Technology NanTong Normal College Jiangsu Nantong226000 China SeGi University Faculty of Engineering Built Environment and Information Technology Kota Damansara Malaysia School of Microelectronics Xidian University Shaanxi Xi'an710000 China

ISBN: (纸本)9798350376548

With the continuous development and popularisation of internet of Things (IoT) technology, the regulation and protection of computer network information security has become increasingly important. The application of IoT information technology enables various devices and systems to communicate and interact with each other, however, it also brings new security challenges and risks. In this context, it is particularly urgent and necessary to develop effective regulation and protection strategies. This paper focuses on computer network information security in the internet of Things environment, considering the rapid development of the internet of Things and its unique security challenges, to study the regulation and protection strategies to adapt to this field. First, this content investigates the shortcomings of traditional information security strategies in dealing with the diversity, large-scale deployment, data privacy protection, real-time monitoring and cross-border integration of the IOT, and discusses the important exploration results and existing defects in the field of IOT security in the current academia and industry. based on a step-by-step exploration of existing references and methods, this content designs a multi-level security protection system that covers security requirements from the device layer to the application layer. In threat detection, the system shows an average of 95% threat detection accuracy, ensuring efficient security monitoring. The system stability and performance evaluation experiment shows that the CPU usage maintenance rate is about 65% on average, and the memory usage is about 55% on average. The above data indicates that the system maintains good stability while operating efficiently. In the adaptive defense mechanism effect test, the system shows an average of about 3 defense mechanism adjustments per day, indicating its high adaptability in a dynamic security environment. The above experimental results jointly verify the effectiv

关键词： Computer Network Protection internet of Things technology Multilayer Security System Protection Mechanism Safety Supervision Strategy

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image Recognition and Position technology based on Super-pixel Fuzzy C-Means Clustering in Industrial Assembly System 3

Image Recognition and Position Technology Based on Super-pix...

引用

3rd international conference on image Processing and Intelligent Control, IPIC 2023

作者： Yuan, Hailiang Sun, Weitao Wang, Hailing Tianjin Vocational College of Mechanics and Electricity Tianjin China Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9781510668140

Improved fuzzy c-means (FCM) clustering algorithms have been widely used for image recognition and localization. However, in industrial assembly systems, the unsatisfactory pixel merging and segmentation results between local adjacent windows, combined with the differences in the shape, size, and material of parts, as well as variations in lighting conditions, make target image recognition and localization a challenge. Most algorithms struggle to achieve the expected results and have high computational complexity. In this study, we propose a super-resolution-based FCM clustering algorithm that is faster and more accurate for image recognition and localization in industrial assembly systems with irregular part sizes. We first use multiscale morphological gradient operations to obtain high-resolution images. Then, we use the fast FCM clustering algorithm to achieve the recognition and extraction of specific target images. Finally, we use the Sobel operator to determine the target's position. The experimental results demonstrate that the proposed algorithm shows higher accuracy and efficiency in image recognition and localization for industrial assembly systems. © 2023 SPIE.

关键词： image recognition

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FMCW ice detection radar signal processing based on improved spectrum estimation algorithm

FMCW ice detection radar signal processing based on improved...

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2024 international conference on image, signal Processing, and Pattern Recognition, ISPP 2024

作者： Song, Yibo Dou, Yinke Wang, Yuchen Zuo, Guangyu Guo, Jingxue Zhang, Zidong School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Shanxi Energy Internet Research Institute Taiyuan China

ISBN: (纸本)9781510680425

The Antarctic ice sheet is an important part of the Earth system and plays a key role in the global climate system. The frequency modulated continuous wave (FMCW) radar can be used to obtain the changes of the transmitted signals at different layers inside the ice sheet, and then the information of the isochronous layers of the ice sheet can be extracted and the shallow accumulation rate can be deduced. In this paper, an improved spectrum estimation algorithm is proposed, which combines FFT (Fast Fourier Transform) and Chirp-Z (CZT transform, linear frequency modulation transform) to estimate the spectrum of the simulated radar system's difference frequency signals, effectively improving the radar detection accuracy, and verifying the effectiveness and rationality of the algorithm, so that the isochronous layers can be extracted on a larger spatial scale. In China's 36th Antarctic scientific expedition, FMCW radar was used to obtain the distribution of shallow isochronous layers in East Antarctica from Zhongshan Station to Taishan Station. In this paper, taking a typical area as an example, the algorithm was used to obtain the stratification and structure information of the ice sheet on a large-scale space, which provides important data support for the calculation of large-scale accumulation rate and flow history in the Antarctic region. © 2024 SPIE.

关键词： Fast Fourier transforms

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Deep Learning-based Modulation Classification Leveraging Dual-Type image 15

Deep Learning-Based Modulation Classification Leveraging Dua...

引用

15th international conference on Information and Communication technology Convergence, ICTC 2024

作者： Cho, Yunseol Kim, Hanvit Park, Hyunwoo Park, Jiyeon Ji, Younggun Ju, Hyungjun Choi, Jaekark Im, Sanghun Kim, Kihun Kim, Sunwoo Hanyang University Department of Electronic Engineering Seoul Korea Republic of Tactical Communication System Team Hanwha Systems Seongnam Korea Republic of

ISBN: (纸本)9798350364637

In this paper, we present an automatic modulation classification (AMC) algorithm for identifying overlapped signals. The proposed algorithm leverages dual-type images as deep learning input data, which is composed of spectrogram and signal images. The dual-type images have the features of both individual images, such as frequency change over time and information on amplitude and phase. We improve modulation classification performance by reflecting various features of a single signal. The simulation results show that the proposed algorithm has accurate classification performance compared to single-type input images, especially in analog modulation classification. © 2024 IEEE.

关键词： signal modulation

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Fragile watermarking for medical image authentication based on DCT technique 5

Fragile watermarking for medical image authentication based ...

引用

5th international conference on Pattern Analysis and Intelligent systems, PAIS 2023

作者： Bouarroudj, Riadh Souami, Feryel Bellala, Fatma Zohra University of Science and Technology Houari Boumediene Computer Science Department Algiers Algeria

ISBN: (纸本)9798350381450

With the advancement of internet and computer technology in the last decade, the ease of editing and altering digital images has significantly increased. Therefore, it is now more crucial than ever for sensitive industries, such as the medical field, to employ image authentication techniques in order to ensure that the images have not been altered. This paper presents a non-blind fragile watermarking technique for medical image authentication. The watermark is generated by downsampling the cover image and embedded into the high-frequency coefficients after applying DCT to the host image. The experimental results demonstrate that the presented technique produces a high watermarked image quality and offers a high sensitivity to various attacks like JPEG compression, collage, and vector quantization. Furthermore, the model localizes with high accuracy the tampered areas within the attacked image. © 2023 IEEE.

关键词： Authentication

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2023 5th international Symposium on signal Processing systems, SSPS 2023

2023 5th International Symposium on Signal Processing System...

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5th international Symposium on signal Processing systems, SSPS 2023

ISBN: (纸本)9798400700040

The proceedings contain 11 papers. The topics discussed include: accurate shadow height measurement technology of the SAR image;millimeter wave radar fall detection algorithm based on improved transformer;an end-to-end learning based covolutional neural network for single image defogging algorithm;ornaments and barlines recognition of numbered musical notation using YOLOv5;study on hyperspectral remote sensing images of GF-5 de-blurring based on sparse representation;design and implementation of target tracking system in low illumination environment based on FPGA;SAR image geometry correction technology based on block parallel signal processing;speech recognition method based on deep learning of artificial intelligence: an example of BLSTM-CTC model;and high precision reference measurement technology for mechanical scanning radar.

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The Method of Industrial internet image Super-resolution based on Transformer 16

The Method of Industrial Internet Image Super-resolution Bas...

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16th IEEE international conference on signal Processing (ICSP)

作者： Liu, Lin Yu, Yingjie Wang, Juncheng Jin, Yi Zeng, Yuqiao China Automot Technol & Res Ctr Co Ltd Automot Data China Tianjin Co Ltd Tianjin Peoples R China Beijing Jiaotong Univ Inst Informat Sci Beijing Peoples R China

ISBN: (数字)9781665460569

ISBN: (纸本)9781665460569

As a fundamental task in the field of computer vision, super-resolution reconstruction has a wide range of applications on the industrial internet. However, most of the existing super-resolution reconstruction methods are based on convolutional neural networks for feature extraction, which have the problems of low model representation efficiency and insufficient explanation of the extraction process, which limit the performance of the model in industrial internet scenarios. In recent years, although transformers have been proposed to solve the above problems well and achieve good results in image classification tasks, there is still room for improvement in the adaptability of super-resolution reconstruction tasks. Therefore, in this paper, an improved transformer-based image super-resolution reconstruction model is designed to effectively improve the performance of the image super-resolution reconstruction model. Experiments show that the adaptation of the Transformer mechanism on the super-resolution reconstruction task in this paper can practically improve the performance of the model on public datasets and industrial internet scenario datasets.

关键词： Super-resolution Reconstruction Transformer Technologies Industrial internet

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