The counterfeit brand cosmetics made available on the market have always been a widespread concern. Traditional anti-counterfeiting schemes usually focus on the authenticity of brand cosmetics. However, verifying the identity of the sales counter is also a challenging issue to be solved. In this paper, we propose a new authentication protocol for brand cosmetics anti-counterfeiting system which is used for checking the identity of sales counter and the authenticity of brand cosmetics. The sales counter authenticated by the anticounterfeiting server obtains a cosmetic authentication confirmation about the authenticity of the brand cosmetic. Besides, the security of proposed protocol is proved by informally analysis. Performance evaluation shows that the proposed protocol is efficiency.
{"title":"An Efficient Authentication Protocol for Brand Cosmetics Anti-Counterfeiting System","authors":"Xiangwei Meng, Qingchun Yu, Wei Lang, Yufeng Liang, Zisang Xu, Kuan-Ching Li","doi":"10.1109/cscloud-edgecom58631.2023.00029","DOIUrl":"https://doi.org/10.1109/cscloud-edgecom58631.2023.00029","url":null,"abstract":"The counterfeit brand cosmetics made available on the market have always been a widespread concern. Traditional anti-counterfeiting schemes usually focus on the authenticity of brand cosmetics. However, verifying the identity of the sales counter is also a challenging issue to be solved. In this paper, we propose a new authentication protocol for brand cosmetics anti-counterfeiting system which is used for checking the identity of sales counter and the authenticity of brand cosmetics. The sales counter authenticated by the anticounterfeiting server obtains a cosmetic authentication confirmation about the authenticity of the brand cosmetic. Besides, the security of proposed protocol is proved by informally analysis. Performance evaluation shows that the proposed protocol is efficiency.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"6 1","pages":"120-125"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73065180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Natural language processing technology is an important research area in artificial intelligence which occupies a pivotal position in deep learning. This paper describes in detail the research of NLP based on Transformer structure, thus showing its ultra-high performance and development prospects. Therefore, this article provides a detailed description of the research on NLP based on the Transformer structure, in order to demonstrate its ultra-high performance and development prospects.
{"title":"NLP Research Based on Transformer Model","authors":"Junjie Wu, Xueting Huang, Jingnian Liu, Yingzi Huo, Gaojing Yuan, Ronglin Zhang","doi":"10.1109/CSCloud-EdgeCom58631.2023.00065","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00065","url":null,"abstract":"Natural language processing technology is an important research area in artificial intelligence which occupies a pivotal position in deep learning. This paper describes in detail the research of NLP based on Transformer structure, thus showing its ultra-high performance and development prospects. Therefore, this article provides a detailed description of the research on NLP based on the Transformer structure, in order to demonstrate its ultra-high performance and development prospects.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"140 1","pages":"343-348"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76060919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matrix decomposition is a fundamental operation in linear algebra, and it has various applications in machine learning, signal processing, edge computing, and many other fields. Singular Value Decomposition (SVD) is a matrix decomposition method that can break down a matrix into three matrices: two orthogonal matrices and a diagonal matrix. With the development of domestic high-performance Digital Signal Value Processors (DSP), the demand for matrix computation based on DSP platforms is increasing. The research of SVD implemented based on DSP is important and meaningful. However, accessing the high-performance algorithm requires developers who are familiar with the hardware characteristics, in order to combine the unique features of the algorithm with the limited hardware resources. To reduce the cost of computing the SVD in matrix, we implement a vectorization mapping method for the SVD algorithm on the FT-M7002. The single instruction multiple data (SIMD) instructions embedded in the FT-M7002 processor were utilized to exploit the data-level parallelism in the SVD algorithm. Instead of using data movement and a scalar processing unit (SPU), we compute with a single vector processing element (VPE). Additionally, DMA transfer algorithm is designed to implement matrix transposition and resolve the issue of discontinuous data access. Experimental results show that the optimized SVD algorithm improves execution performance relative to the original SVD algorithm on FT by up to 5.0 ×. Furthermore, we demonstrate that the optimized SVD algorithm on the FT-M7002 performs 1.0-2.0× faster than the optimized SVD algorithm on TMS320C6678 processor.
{"title":"Advancing Matrix Decomposition Efficiency: A Study on FT-Matrix DSP Based SVD Optimization","authors":"Anxing Xie, Yonghua Hu, Aobo Cheng, Zhuoyou Tang, P. Liu, Xin Zhang","doi":"10.1109/CSCloud-EdgeCom58631.2023.00085","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00085","url":null,"abstract":"Matrix decomposition is a fundamental operation in linear algebra, and it has various applications in machine learning, signal processing, edge computing, and many other fields. Singular Value Decomposition (SVD) is a matrix decomposition method that can break down a matrix into three matrices: two orthogonal matrices and a diagonal matrix. With the development of domestic high-performance Digital Signal Value Processors (DSP), the demand for matrix computation based on DSP platforms is increasing. The research of SVD implemented based on DSP is important and meaningful. However, accessing the high-performance algorithm requires developers who are familiar with the hardware characteristics, in order to combine the unique features of the algorithm with the limited hardware resources. To reduce the cost of computing the SVD in matrix, we implement a vectorization mapping method for the SVD algorithm on the FT-M7002. The single instruction multiple data (SIMD) instructions embedded in the FT-M7002 processor were utilized to exploit the data-level parallelism in the SVD algorithm. Instead of using data movement and a scalar processing unit (SPU), we compute with a single vector processing element (VPE). Additionally, DMA transfer algorithm is designed to implement matrix transposition and resolve the issue of discontinuous data access. Experimental results show that the optimized SVD algorithm improves execution performance relative to the original SVD algorithm on FT by up to 5.0 ×. Furthermore, we demonstrate that the optimized SVD algorithm on the FT-M7002 performs 1.0-2.0× faster than the optimized SVD algorithm on TMS320C6678 processor.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"97 1","pages":"464-469"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79203358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.1109/CSCloud-EdgeCom58631.2023.00072
Lan Yang, Chaoyi Yang, Rui Xie, Jingnian Liu, Huan Zhang, Wenjin Tan
Vision is one of the important pathways for human perception of external information, with over 80% of perception being acquired through vision. How to enable computers to possess efficient and flexible visual systems similar to humans has always been a hot topic in the field of computer science. One of the main goals of computer vision research is to reconstruct the geometric structure of 3D objects visible on the visible surfaces from 2D photos. Recently, this technology has become mature enough and its applications range from autonomous driving, virtual reality, cultural heritage preservation and restoration, among others, with significant research value. In this paper, we summarize the key technical issues in 3D reconstruction from existing technologies, first by summarizing traditional methods of 3D reconstruction, then analyzing commonly used deep learning methods for 3D reconstruction and their application scenarios in different fields. Finally, we conclude and provide an outlook on future development directions.
{"title":"3D Reconstruction From Traditional Methods to Deep Learning","authors":"Lan Yang, Chaoyi Yang, Rui Xie, Jingnian Liu, Huan Zhang, Wenjin Tan","doi":"10.1109/CSCloud-EdgeCom58631.2023.00072","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00072","url":null,"abstract":"Vision is one of the important pathways for human perception of external information, with over 80% of perception being acquired through vision. How to enable computers to possess efficient and flexible visual systems similar to humans has always been a hot topic in the field of computer science. One of the main goals of computer vision research is to reconstruct the geometric structure of 3D objects visible on the visible surfaces from 2D photos. Recently, this technology has become mature enough and its applications range from autonomous driving, virtual reality, cultural heritage preservation and restoration, among others, with significant research value. In this paper, we summarize the key technical issues in 3D reconstruction from existing technologies, first by summarizing traditional methods of 3D reconstruction, then analyzing commonly used deep learning methods for 3D reconstruction and their application scenarios in different fields. Finally, we conclude and provide an outlook on future development directions.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"33 1","pages":"387-392"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81702532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a logistics International Inland Port resource allocation method based on intelligent edge scheduling, and we do a reasonable pre-allocation of logistics resources by building an edge network in the urban system. By using multiple integrated learning models and regional prevalence classification algorithms, the distribution demand of each sub-distribution point is predicted. The proposed method is able to cope with uncertainties such as high distribution volume, variable distribution situations or long transportation distances. We use the HuaiHua International Inland Port as the simulation object, and the simulation results show that the proposed method has the highest efficiency in logistics distribution and is still highly adaptive in emergency situations.
{"title":"Research on Fast Adaptive Transmission Models for International Inland Port Based on Edge Intelligence","authors":"Yiwen Liu, Zhirong Zhu, Tangyan, Wenkan Wen, Xiaoning Peng, Yuanquan Shi","doi":"10.1109/CSCloud-EdgeCom58631.2023.00062","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00062","url":null,"abstract":"In this paper, we propose a logistics International Inland Port resource allocation method based on intelligent edge scheduling, and we do a reasonable pre-allocation of logistics resources by building an edge network in the urban system. By using multiple integrated learning models and regional prevalence classification algorithms, the distribution demand of each sub-distribution point is predicted. The proposed method is able to cope with uncertainties such as high distribution volume, variable distribution situations or long transportation distances. We use the HuaiHua International Inland Port as the simulation object, and the simulation results show that the proposed method has the highest efficiency in logistics distribution and is still highly adaptive in emergency situations.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"27 1","pages":"324-329"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81777847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.1109/CSCloud-EdgeCom58631.2023.00019
Zhiqiang Ruan, Yuchen Yang, Lejia Chen
This paper investigates a new attack method called "near-source attack". It leverages the broadcast frames of the 802.11 protocol to establish a hidden tunnel and bypass physical isolation networks or air-gapped networks. We first analyze and implement a common technology known as Ghost Tunnel, which allows the attacker to control the target host and transmit information without being detected. However, this method suffers from frame loss, repeated frame, and attack transparency. We then propose an improved solution to deliver malicious programs to the target host using a modified BadUSB hardware device. Once the attackers successfully get in the isolated networks, they can bypass security protection devices and exploit vulnerabilities of communication protocols, so that they can remote control of target devices and hidden data transmission. We further conducted experiments to verify the feasibility and effectiveness of this attack scheme. The results indicate that the attack logic is capable of inducing the target host to engage in covert communication. Finally, we give some defense measures for such attacks.
{"title":"Near-Source Attack for Isolated Networks with Covert Channel Transmission","authors":"Zhiqiang Ruan, Yuchen Yang, Lejia Chen","doi":"10.1109/CSCloud-EdgeCom58631.2023.00019","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00019","url":null,"abstract":"This paper investigates a new attack method called \"near-source attack\". It leverages the broadcast frames of the 802.11 protocol to establish a hidden tunnel and bypass physical isolation networks or air-gapped networks. We first analyze and implement a common technology known as Ghost Tunnel, which allows the attacker to control the target host and transmit information without being detected. However, this method suffers from frame loss, repeated frame, and attack transparency. We then propose an improved solution to deliver malicious programs to the target host using a modified BadUSB hardware device. Once the attackers successfully get in the isolated networks, they can bypass security protection devices and exploit vulnerabilities of communication protocols, so that they can remote control of target devices and hidden data transmission. We further conducted experiments to verify the feasibility and effectiveness of this attack scheme. The results indicate that the attack logic is capable of inducing the target host to engage in covert communication. Finally, we give some defense measures for such attacks.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"1068 1","pages":"59-64"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88107047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.1109/cscloud-edgecom58631.2023.00003
{"title":"Copyright","authors":"","doi":"10.1109/cscloud-edgecom58631.2023.00003","DOIUrl":"https://doi.org/10.1109/cscloud-edgecom58631.2023.00003","url":null,"abstract":"","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"6 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85585884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.1109/cscloud-edgecom58631.2023.00008
{"title":"Message from the Program Chairs - EdgeCom 2023","authors":"","doi":"10.1109/cscloud-edgecom58631.2023.00008","DOIUrl":"https://doi.org/10.1109/cscloud-edgecom58631.2023.00008","url":null,"abstract":"","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"371 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84928707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.1109/CSCloud-EdgeCom58631.2023.00055
Yuelong Liu, Zhuo Xu, Jian Lin, Jianlong Xu, Lingru Cai
In the era of big data, QoS prediction is crucial for providing high-quality cloud services. However, conventional centralized approaches may pose privacy risks as they require users to upload QoS data. Additionally, variations in geographic and network environments can lead to QoS data heterogeneity, making it difficult to achieve learning efficiency with traditional methods. To address the privacy and heterogeneity issues, we propose a novel federated matrix factorization method with model similarity awareness for QoS prediction, called MSA-Fed. MSA-Fed clusters the local models uploaded by users during the learning process and performs differential aggregation and assignments of global models based on the clustering results. We evaluated the proposed framework on a publicly available and widely used real-world QoS dataset, and the experimental results demonstrate the effectiveness of MSA-Fed in achieving accurate QoS prediction, improving communication efficiency and maintaining users’ privacy.
{"title":"MSA-Fed: Model Similarity Aware Federated Learning for Data Heterogeneous QoS Prediction","authors":"Yuelong Liu, Zhuo Xu, Jian Lin, Jianlong Xu, Lingru Cai","doi":"10.1109/CSCloud-EdgeCom58631.2023.00055","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00055","url":null,"abstract":"In the era of big data, QoS prediction is crucial for providing high-quality cloud services. However, conventional centralized approaches may pose privacy risks as they require users to upload QoS data. Additionally, variations in geographic and network environments can lead to QoS data heterogeneity, making it difficult to achieve learning efficiency with traditional methods. To address the privacy and heterogeneity issues, we propose a novel federated matrix factorization method with model similarity awareness for QoS prediction, called MSA-Fed. MSA-Fed clusters the local models uploaded by users during the learning process and performs differential aggregation and assignments of global models based on the clustering results. We evaluated the proposed framework on a publicly available and widely used real-world QoS dataset, and the experimental results demonstrate the effectiveness of MSA-Fed in achieving accurate QoS prediction, improving communication efficiency and maintaining users’ privacy.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"36 1","pages":"281-286"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83811739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.1109/CSCloud-EdgeCom58631.2023.00067
Weidong Xiao, Wenjin Tan, Naixue Xiong, Ce Yang, Lin Chen, Rui Xie
Emotion recognition refers to the process of actively analyzing human emotions through computer technology, and it has become an important part of modern society. Traditional emotion recognition is mainly based on a single information source, such as text, speech, video, etc., from which emotional features are extracted for classification or regression to recognize human emotions. With the development of artificial intelligence technology, multimodal emotion recognition is gradually becoming widely used. It combines two or more types of information, such as text, speech, and visual information, in different ways to analyze emotions. Multimodal emotion recognition is far superior to a single modality in understanding emotions. This article mainly analyzes the technology of emotion analysis. Firstly, we introduce the basic concepts and research status of emotion recognition. Then, we introduce the main types of emotion recognition and describe various methods used in the process in detail. Finally, we discuss the challenges and future developments of emotion recognition.
{"title":"Deep Learning Emotion Recognition Method","authors":"Weidong Xiao, Wenjin Tan, Naixue Xiong, Ce Yang, Lin Chen, Rui Xie","doi":"10.1109/CSCloud-EdgeCom58631.2023.00067","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00067","url":null,"abstract":"Emotion recognition refers to the process of actively analyzing human emotions through computer technology, and it has become an important part of modern society. Traditional emotion recognition is mainly based on a single information source, such as text, speech, video, etc., from which emotional features are extracted for classification or regression to recognize human emotions. With the development of artificial intelligence technology, multimodal emotion recognition is gradually becoming widely used. It combines two or more types of information, such as text, speech, and visual information, in different ways to analyze emotions. Multimodal emotion recognition is far superior to a single modality in understanding emotions. This article mainly analyzes the technology of emotion analysis. Firstly, we introduce the basic concepts and research status of emotion recognition. Then, we introduce the main types of emotion recognition and describe various methods used in the process in detail. Finally, we discuss the challenges and future developments of emotion recognition.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"126 1","pages":"357-362"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88681919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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