This paper mainly summarizes and introduces the improvements proposed by scholars at home and abroad in recent years for the application of Rapidly-exploring Random Tree in robot arms. This paper first briefly introduces the existing path planning algorithms and expounds their advantages and disadvantages. Then the principle and process of Rapidly-exploring Random Tree are described and the RRT algorithm in three-dimensional space is simulated and analyzed. Next, the improved RRT algorithm proposed by domestic and foreign researchers is classified, analyzed and explained. Finally, the whole article is summarized and the direction of future development and research of manipulator motion planning algorithms is prospected.
{"title":"Improved Motion Planning Algorithms Based on Rapidly-exploring Random Tree: A Review","authors":"Yixin Wang, Xiaojun Yu, Chuan Yu, Zeming Fan","doi":"10.1145/3571662.3571663","DOIUrl":"https://doi.org/10.1145/3571662.3571663","url":null,"abstract":"This paper mainly summarizes and introduces the improvements proposed by scholars at home and abroad in recent years for the application of Rapidly-exploring Random Tree in robot arms. This paper first briefly introduces the existing path planning algorithms and expounds their advantages and disadvantages. Then the principle and process of Rapidly-exploring Random Tree are described and the RRT algorithm in three-dimensional space is simulated and analyzed. Next, the improved RRT algorithm proposed by domestic and foreign researchers is classified, analyzed and explained. Finally, the whole article is summarized and the direction of future development and research of manipulator motion planning algorithms is prospected.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125579176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. A. P. Ratna, Prima Dewi Purnamasari, Nadhifa Khalisha Anandra, Dyah Lalita Luhurkinanti
This paper discusses the development of an Automatic Essay Grading System (SIMPLE-O) designed using hybrid CNN and Bidirectional LSTM and Manhattan Distance for Japanese language course essay grading. The most stable and best model is trained using hyperparameters with kernel sizes of 5, filters or CNN outputs of 64, a pool size of 4, Bidirectional LSTM units of 50, and a batch size of 64. The deep learning model is trained using the Adam optimizer with a learning rate of 0.001, an epoch of 25, and using an L1 regularization of 0.01. The average error obtained is 29%.
{"title":"Hybrid Deep Learning CNN-Bidirectional LSTM and Manhattan Distance for Japanese Automated Short Answer Grading: Use case in Japanese Language Studies","authors":"A. A. P. Ratna, Prima Dewi Purnamasari, Nadhifa Khalisha Anandra, Dyah Lalita Luhurkinanti","doi":"10.1145/3571662.3571666","DOIUrl":"https://doi.org/10.1145/3571662.3571666","url":null,"abstract":"This paper discusses the development of an Automatic Essay Grading System (SIMPLE-O) designed using hybrid CNN and Bidirectional LSTM and Manhattan Distance for Japanese language course essay grading. The most stable and best model is trained using hyperparameters with kernel sizes of 5, filters or CNN outputs of 64, a pool size of 4, Bidirectional LSTM units of 50, and a batch size of 64. The deep learning model is trained using the Adam optimizer with a learning rate of 0.001, an epoch of 25, and using an L1 regularization of 0.01. The average error obtained is 29%.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116421963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a key technology to solve the problem of trust in application systems, blockchain has attracted more and more attention in recent years. Many researches focus on applying voting-based consensus in permissionless blockchain to improve the throughput. However, in these methods, mute nodes may get the reward without participating in consensus, which may impact the availability of the system. We propose an observation exchanging protocol based on double-chain architecture to detect mute nodes. Nodes will vote on whether other nodes have sent protocol messages, and agree on an observation matrix which is generated by merging the observation of all nodes through consensus. We also propose an incentive mechanism and adopt a reputation system based on the matrix to punish mute nodes. Block reward is divided into three parts and is distributed according to the observation matrix. Security analysis shows that the observation exchanging protocol ensures mute nodes can be detected, and the incentive mechanism ensures mute nodes and the nodes adopt selfish strategies can be punished. Finally, we implement a prototype to evaluate our observation exchanging protocol and incentive mechanism. Experiment shows that the observation exchanging protocol merely has small influence on consensus delay.
{"title":"Detecting and Punishing Mute Nodes in Shard-Based Permissionless Blockchains","authors":"Mufei Qiu, Tianyu Kang, Li Guo, Wenwei Huang","doi":"10.1145/3571662.3571680","DOIUrl":"https://doi.org/10.1145/3571662.3571680","url":null,"abstract":"As a key technology to solve the problem of trust in application systems, blockchain has attracted more and more attention in recent years. Many researches focus on applying voting-based consensus in permissionless blockchain to improve the throughput. However, in these methods, mute nodes may get the reward without participating in consensus, which may impact the availability of the system. We propose an observation exchanging protocol based on double-chain architecture to detect mute nodes. Nodes will vote on whether other nodes have sent protocol messages, and agree on an observation matrix which is generated by merging the observation of all nodes through consensus. We also propose an incentive mechanism and adopt a reputation system based on the matrix to punish mute nodes. Block reward is divided into three parts and is distributed according to the observation matrix. Security analysis shows that the observation exchanging protocol ensures mute nodes can be detected, and the incentive mechanism ensures mute nodes and the nodes adopt selfish strategies can be punished. Finally, we implement a prototype to evaluate our observation exchanging protocol and incentive mechanism. Experiment shows that the observation exchanging protocol merely has small influence on consensus delay.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127050526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since the task of hit song prediction was proposed, many experts and technicians have done a lot of research and achieved good results, but there are still some problems such as limited song feature types, lack of feature importance, and insufficient prediction accuracy. This paper proposes a song popularity prediction model based on multi-modal feature fusion and LightGBM. In our proposed model, there is a multi-modal feature extraction structure, a LightGBM structure and a logistic regression structure. First, in order to solve the problem of limited song feature types, we fuse metadata, audio features and other relevant important features into multi-modal features. Then, in order to improve the accuracy of prediction, we introduce LightGBM algorithm to preprocess the dataset and train the model, so as to obtain the predicted value of song popularity. At the same time, we introduce a logistic regression model to research the influence of each feature on whether a song is popular from the perspective of binary classification, so that we can further study the importance of song features, and obtain the response coefficient of each feature, namely, the coefficient of response mean. Finally, we compare the prediction results of our model with the existing models, and the experiments show that the prediction results of our model have higher accuracy.
{"title":"Song popularity prediction model based on multi-modal feature fusion and LightGBM","authors":"Huafeng Zeng, Qiang Yuan, Li Guo, Shibiao Xu","doi":"10.1145/3571662.3571667","DOIUrl":"https://doi.org/10.1145/3571662.3571667","url":null,"abstract":"Since the task of hit song prediction was proposed, many experts and technicians have done a lot of research and achieved good results, but there are still some problems such as limited song feature types, lack of feature importance, and insufficient prediction accuracy. This paper proposes a song popularity prediction model based on multi-modal feature fusion and LightGBM. In our proposed model, there is a multi-modal feature extraction structure, a LightGBM structure and a logistic regression structure. First, in order to solve the problem of limited song feature types, we fuse metadata, audio features and other relevant important features into multi-modal features. Then, in order to improve the accuracy of prediction, we introduce LightGBM algorithm to preprocess the dataset and train the model, so as to obtain the predicted value of song popularity. At the same time, we introduce a logistic regression model to research the influence of each feature on whether a song is popular from the perspective of binary classification, so that we can further study the importance of song features, and obtain the response coefficient of each feature, namely, the coefficient of response mean. Finally, we compare the prediction results of our model with the existing models, and the experiments show that the prediction results of our model have higher accuracy.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121289125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a residual dense networks (RDN)-based image super-resolution method using Meta-learning. Specifically, deep extraction of global features is performed on the external dataset through an RDN, meta-learning to obtain an initial parameter definitely for internal learning, so we can utilize both external and internal data. Our method achieves good results with only one gradient update. And it can be appropriate for image super-resolution under the action of different blur kernels, with a wider application range and high flexibility.
{"title":"AN RDN-based image super-resolution method using Meta-learning","authors":"Jue Wang, Haoliang Xu, Dan Qiao, Yumo Tian","doi":"10.1145/3571662.3571673","DOIUrl":"https://doi.org/10.1145/3571662.3571673","url":null,"abstract":"In this paper, we propose a residual dense networks (RDN)-based image super-resolution method using Meta-learning. Specifically, deep extraction of global features is performed on the external dataset through an RDN, meta-learning to obtain an initial parameter definitely for internal learning, so we can utilize both external and internal data. Our method achieves good results with only one gradient update. And it can be appropriate for image super-resolution under the action of different blur kernels, with a wider application range and high flexibility.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121650149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: In order to solve the problems of low intelligence and complex deployment of substation auxiliary control system, a new edge gateway system supporting 5g is designed. The gateway system designs a horizontal and vertical data flow mechanism; AI algorithm is applied to automatically classify different scenes of different video streams; Support 5g, WiFi and short-range communication access. The system is highly intelligent and scalable. The actual verification shows that the system is stable, flexible and easy to use.
{"title":"Design of an intelligent substation auxiliary control edge gateway system supporting 5G","authors":"Chun Zhu, Bingjie Liu, Xiaoyu Zhao","doi":"10.1145/3571662.3571686","DOIUrl":"https://doi.org/10.1145/3571662.3571686","url":null,"abstract":"Abstract: In order to solve the problems of low intelligence and complex deployment of substation auxiliary control system, a new edge gateway system supporting 5g is designed. The gateway system designs a horizontal and vertical data flow mechanism; AI algorithm is applied to automatically classify different scenes of different video streams; Support 5g, WiFi and short-range communication access. The system is highly intelligent and scalable. The actual verification shows that the system is stable, flexible and easy to use.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129647421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Bambang Hidayanto, Sendy Prayogo, M. Lubis
The digital era, which is a jargon in welcoming the technological developments has given birth to a new form of learning that eliminates the requirement of physical presence of teachers and students within the same place and time, or it can be known as Online Learning. The possibility for the institution of education in supporting their business into a new level of services in supporting their ecosystem have met the challenges of the readiness in doing the transformation from the traditional learning within the context of human resources, technology, and learning concept into a syllabus with the purpose of achieving the same level or output. When the Corona Virus Diseases 19 (COVID 19) made drastic changes in every aspect that afterwards became a global pandemic, the implementation of online learning would ensure the survivability of the educational institution in keeping their business. Telkom University, as one of private university in Indonesia, with the student body almost reaches 30.000, uses Learning Management System (LMS) in enabling the learning activities as the primary solution but has a problem in ensuring no cheating activities during the examination. As the common approach in ensuring the integrity of online examination through LMS with the creation of question bank and randomize the question is seen as not efficient, the institution also tries to monitor and control with the implementation of video conference-based application like ZOOM and Safe Exam Browser (SEB), but raises another problem in cost, compatibility issues, and motivation issues. Proctoring has become another approach that is recently has continue evolving with the involvement from Artificial Intelligence (AI) in doing the facial recognition. This research will develop the proctoring tools that can be integrated with the LMS used in Telkom University as the strategy in preventing misconduct behavior that led to academic cheating in online examination.
{"title":"Designing Web Based Proctoring System for Online Examination (SPIRIT 1.0) in Telkom University","authors":"Muhammad Bambang Hidayanto, Sendy Prayogo, M. Lubis","doi":"10.1145/3571662.3571669","DOIUrl":"https://doi.org/10.1145/3571662.3571669","url":null,"abstract":"The digital era, which is a jargon in welcoming the technological developments has given birth to a new form of learning that eliminates the requirement of physical presence of teachers and students within the same place and time, or it can be known as Online Learning. The possibility for the institution of education in supporting their business into a new level of services in supporting their ecosystem have met the challenges of the readiness in doing the transformation from the traditional learning within the context of human resources, technology, and learning concept into a syllabus with the purpose of achieving the same level or output. When the Corona Virus Diseases 19 (COVID 19) made drastic changes in every aspect that afterwards became a global pandemic, the implementation of online learning would ensure the survivability of the educational institution in keeping their business. Telkom University, as one of private university in Indonesia, with the student body almost reaches 30.000, uses Learning Management System (LMS) in enabling the learning activities as the primary solution but has a problem in ensuring no cheating activities during the examination. As the common approach in ensuring the integrity of online examination through LMS with the creation of question bank and randomize the question is seen as not efficient, the institution also tries to monitor and control with the implementation of video conference-based application like ZOOM and Safe Exam Browser (SEB), but raises another problem in cost, compatibility issues, and motivation issues. Proctoring has become another approach that is recently has continue evolving with the involvement from Artificial Intelligence (AI) in doing the facial recognition. This research will develop the proctoring tools that can be integrated with the LMS used in Telkom University as the strategy in preventing misconduct behavior that led to academic cheating in online examination.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126687174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The grain size is an important steel grading parameter. For metallographic steel images with various grain sizes and complex textures, it is not possible for a human expert to determine the grain size efficiently. Meanwhile, conventional computer vision models are designed based on general images and they are not capable of achieving high performance in metallographic steel grain size recognition. To solve these problems, a method based on multiple receptive field fusion is proposed. A multi-scale convolutional net is used to extract information of microstructures in various scales. In addition, to augment the extracted features, a self-attention module is used to improve the robustness of feature representation with complex metallographic textures. At last, via a multiple feature fusion module, the data capacity is extended by projecting features into multiple hidden spaces. A comprehensive experiment was conducted on the Huawei Cloud Dataset and the classification accuracy was improved by 27% compared with other SOTA models, while our computation cost was only 0.06 GFLOPs.
{"title":"MFFNet: Multi-Receptive Field Fusion Net for Microscope Steel Grain Grading","authors":"Jiaxi Sun, Jiguang Zhang, Shibiao Xu, Weiliang Meng, Xiaopeng Zhang","doi":"10.1145/3571662.3571670","DOIUrl":"https://doi.org/10.1145/3571662.3571670","url":null,"abstract":"The grain size is an important steel grading parameter. For metallographic steel images with various grain sizes and complex textures, it is not possible for a human expert to determine the grain size efficiently. Meanwhile, conventional computer vision models are designed based on general images and they are not capable of achieving high performance in metallographic steel grain size recognition. To solve these problems, a method based on multiple receptive field fusion is proposed. A multi-scale convolutional net is used to extract information of microstructures in various scales. In addition, to augment the extracted features, a self-attention module is used to improve the robustness of feature representation with complex metallographic textures. At last, via a multiple feature fusion module, the data capacity is extended by projecting features into multiple hidden spaces. A comprehensive experiment was conducted on the Huawei Cloud Dataset and the classification accuracy was improved by 27% compared with other SOTA models, while our computation cost was only 0.06 GFLOPs.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114068315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, with the development of unmanned vehicle fields, the millimeter wave radar has also developed rapidly and has been applied to many systems. Frequency modulated continuous wave (FMCW) radar has become a hot research topic in millimeter radar areas due to its physical characteristics, including strong sensing capability and high resolution. This paper investigates gesture recognition applications based on FMCW radar and summarizes the latest research using FMCW radar system. Firstly, this paper reviews existing gesture recognition applications using wireless signals. Secondly, it focuses on the FMCW radar gesture recognition system and gives the general framework of gesture recognition, including gesture data acquisition, signal preprocessing, gesture recognition algorithm and classification results. Next, it analyzes the typical gesture recognition application systems from coarse-grained and fine-grained granularity and elaborates experimental scenes, experimental equipment, gesture types, signal preprocessing and classification methods. Finally, it presents the challenges and issues involved in gesture recognition based on FMCW radar and proposes future research directions.
{"title":"A Survey of Hand Gesture Recognition Based on FMCW Radar","authors":"Zhengjie Wang, Fei Liu, Xue Li, Mingjing Ma, Xiaoxue Feng, Yinjing Guo","doi":"10.1145/3571662.3571674","DOIUrl":"https://doi.org/10.1145/3571662.3571674","url":null,"abstract":"In recent years, with the development of unmanned vehicle fields, the millimeter wave radar has also developed rapidly and has been applied to many systems. Frequency modulated continuous wave (FMCW) radar has become a hot research topic in millimeter radar areas due to its physical characteristics, including strong sensing capability and high resolution. This paper investigates gesture recognition applications based on FMCW radar and summarizes the latest research using FMCW radar system. Firstly, this paper reviews existing gesture recognition applications using wireless signals. Secondly, it focuses on the FMCW radar gesture recognition system and gives the general framework of gesture recognition, including gesture data acquisition, signal preprocessing, gesture recognition algorithm and classification results. Next, it analyzes the typical gesture recognition application systems from coarse-grained and fine-grained granularity and elaborates experimental scenes, experimental equipment, gesture types, signal preprocessing and classification methods. Finally, it presents the challenges and issues involved in gesture recognition based on FMCW radar and proposes future research directions.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128919322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhengtao Sun, Bo Liu, Boyang Zhang, Faguo Wu, Bo Zhou, Hao Wu
The supply chain refers to the process that starts from the production of parts, goes through transportation, storage and other processes, and finally forms products and sells them. The supply chain generally consists of suppliers, manufacturers, sales companies, consumers and other elements. With the increase in the scale of the supply chain and the increase in transactions, it becomes difficult to track the transportation process of goods, and the transaction reliability is low, which leads to problems such as low logistics and transportation efficiency, difficulty in market supervision, and difficulty in confirming the ownership of goods. Therefore, we need a means to informatize the supply chain. Blockchain consists of blocks containing information connected in chronological order. Compared with traditional networks, blockchain has two core characteristics: one is the immutability of data, and the other is decentralization. Its structure naturally fit the characteristics and development trend of the supply chain, so we can consider using blockchain technology to solve the problems in the supply chain, so as to realize the innovative development of the supply chain. Our article first gives the concrete scheme of applying blockchain technology to supply chains. From the four aspects of data collection, uploading, storage and use, we discussed how those various blockchain privacy protection technologies protect and enhance data privacy in the supply chain, including public key cryptography, digital signature, secret sharing technology, threshold cryptography, access control, and secure multi-party computation. We also predict the possible development direction of blockchain technology which is applied to supply chain.
{"title":"Privacy Protection Technology in Supply Chain-oriented Blockchain","authors":"Zhengtao Sun, Bo Liu, Boyang Zhang, Faguo Wu, Bo Zhou, Hao Wu","doi":"10.1145/3571662.3571677","DOIUrl":"https://doi.org/10.1145/3571662.3571677","url":null,"abstract":"The supply chain refers to the process that starts from the production of parts, goes through transportation, storage and other processes, and finally forms products and sells them. The supply chain generally consists of suppliers, manufacturers, sales companies, consumers and other elements. With the increase in the scale of the supply chain and the increase in transactions, it becomes difficult to track the transportation process of goods, and the transaction reliability is low, which leads to problems such as low logistics and transportation efficiency, difficulty in market supervision, and difficulty in confirming the ownership of goods. Therefore, we need a means to informatize the supply chain. Blockchain consists of blocks containing information connected in chronological order. Compared with traditional networks, blockchain has two core characteristics: one is the immutability of data, and the other is decentralization. Its structure naturally fit the characteristics and development trend of the supply chain, so we can consider using blockchain technology to solve the problems in the supply chain, so as to realize the innovative development of the supply chain. Our article first gives the concrete scheme of applying blockchain technology to supply chains. From the four aspects of data collection, uploading, storage and use, we discussed how those various blockchain privacy protection technologies protect and enhance data privacy in the supply chain, including public key cryptography, digital signature, secret sharing technology, threshold cryptography, access control, and secure multi-party computation. We also predict the possible development direction of blockchain technology which is applied to supply chain.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131902531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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