Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9302008
Yung-Chang Lai, C. Kao, Jhih-Dao Jhan, Fei-Hua Kuo, C. Chang, Tai-Chueh Shih
With the development of Information Technology (IT) and Software-Defined Networking (SDN), Communications Service Providers (CSPs) can collect much information from telecommunication circuits. However, some of the existing circuit measurement has not been used well. For CSPs, it is important to find more efficient ways of utilizing the circuit measurement, e.g., delay, jitter, packet loss, and speed-test results for customer satisfaction. One of the most popular ways is to use speed-test tools (such as Speedtest online) to measure the service rate of the application layer. However, it is difficult to justify whether the telecommunication circuit is normal or not. For example, when the speed-test result of a specific circuit is 90 Mbps, the physical line rate may be 100Mbps. To address the above issues, we first investigate the measurement and management mechanisms of the existing telecommunications networks, including the core components and protocols. In this paper, we leverage artificial intelligence (AI) technologies to predict whether customers complain or not. We evaluate the proposed AI model by using the real data from telecommunication circuits and analyze the key performance metrics.
{"title":"Quality of Service Measurement and Prediction through AI Technology","authors":"Yung-Chang Lai, C. Kao, Jhih-Dao Jhan, Fei-Hua Kuo, C. Chang, Tai-Chueh Shih","doi":"10.1109/ECICE50847.2020.9302008","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9302008","url":null,"abstract":"With the development of Information Technology (IT) and Software-Defined Networking (SDN), Communications Service Providers (CSPs) can collect much information from telecommunication circuits. However, some of the existing circuit measurement has not been used well. For CSPs, it is important to find more efficient ways of utilizing the circuit measurement, e.g., delay, jitter, packet loss, and speed-test results for customer satisfaction. One of the most popular ways is to use speed-test tools (such as Speedtest online) to measure the service rate of the application layer. However, it is difficult to justify whether the telecommunication circuit is normal or not. For example, when the speed-test result of a specific circuit is 90 Mbps, the physical line rate may be 100Mbps. To address the above issues, we first investigate the measurement and management mechanisms of the existing telecommunications networks, including the core components and protocols. In this paper, we leverage artificial intelligence (AI) technologies to predict whether customers complain or not. We evaluate the proposed AI model by using the real data from telecommunication circuits and analyze the key performance metrics.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126196574","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9301977
Jyh-Wei Chen
This paper proposes an analysis of subsampled image size for detection and identification of brake pad contours by using deep learning for the automatic detection systems. In brake pad manufacture, some problems may occur such as expansion, missing corners at the edges so that the edges of the brake pad need to obtain before checking missing corners. The size of subsampled image for training and testing for machine learning is very significant factor for optimized and efficient feature extraction. The size of subsampled image has great impact on detection and identification for feature extraction determines the accuracy of prediction of deep learning. The images are evaluated through loss function in order to observe the training process of the models. The experimental results show the method to determine subsampled image size to have better accuracy.
{"title":"Analysis of Subsampled Image Size for Detection and Identification of Brake Pad Contours by Using Deep Learning","authors":"Jyh-Wei Chen","doi":"10.1109/ECICE50847.2020.9301977","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9301977","url":null,"abstract":"This paper proposes an analysis of subsampled image size for detection and identification of brake pad contours by using deep learning for the automatic detection systems. In brake pad manufacture, some problems may occur such as expansion, missing corners at the edges so that the edges of the brake pad need to obtain before checking missing corners. The size of subsampled image for training and testing for machine learning is very significant factor for optimized and efficient feature extraction. The size of subsampled image has great impact on detection and identification for feature extraction determines the accuracy of prediction of deep learning. The images are evaluated through loss function in order to observe the training process of the models. The experimental results show the method to determine subsampled image size to have better accuracy.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128229447","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9301965
Yih-Cherng Lee, Jian-Jiun Ding, L. Yeung, Tay-Wey Lee, Chia-Jung Chang, Yu-Tze Lin
The foveal avascular zone (FAZ) is a region on a retinal image where blood vessels distribute sparsely. It helps identify diabetic retinopathy. In this study, we investigate the optical coherence tomography angiography (OCTA) to analyze the extent of the FAZ more precisely. Moreover, a learning-based denoising architecture is applied to well distinguish the vascular vessel and the noise. With these techniques, the FAZ in an OCTA image can be well extracted and its area can be estimated accurately.
{"title":"Algorithm of Foveal Avascular Zone Detection with Denoising Mechanism Learning on Optical Coherence Tomography Angiography Images","authors":"Yih-Cherng Lee, Jian-Jiun Ding, L. Yeung, Tay-Wey Lee, Chia-Jung Chang, Yu-Tze Lin","doi":"10.1109/ECICE50847.2020.9301965","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9301965","url":null,"abstract":"The foveal avascular zone (FAZ) is a region on a retinal image where blood vessels distribute sparsely. It helps identify diabetic retinopathy. In this study, we investigate the optical coherence tomography angiography (OCTA) to analyze the extent of the FAZ more precisely. Moreover, a learning-based denoising architecture is applied to well distinguish the vascular vessel and the noise. With these techniques, the FAZ in an OCTA image can be well extracted and its area can be estimated accurately.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130686084","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9301991
Quang-Phuoc Tran, T. Le, Shyh-Chour Huang
This study aims to prove the influence of wetness on the mechanical characteristic of carbon fiber–reinforced plastic (CFRP). There is no suitable method for using lubrication fluids in the composite industry. There is a significant impact on CFRP machining capabilities by the geometry of the cutting tool and cryogenic liquid cooling. This paper selects the optimal parametric combinations of the carbon fiber reinforced plastic drilling process by using Taguchi optimization technique base on grey relation analysis (GRA) technique (TGRA). The parameters of the drilling process such as the helical angle of the blade, the coolant gas, and the feed rate were found by observing multi-responses output such as surface roughness and diameter of the drill hole. The following parameters resulted in a larger value of grey relational grade (GRG) to reduce the surface roughness and the error deviation of the diameter dimension: the speed of the spindle motor was 6100 rpm, the feed rate was 1006 mm/min, the helical angle of the cutting blade was triple, the coolant gas was CO2-N2 mixture. Finally, an analysis of variance (ANOVA) is used to analyze the effect of each parameter process in the estimation of GRG. The results showed that the coolant gas had an outstanding effect on the surface roughness and error deviation of the diameter dimension.
{"title":"Optimization of CFRP Drilling Process with Multi-Criteria Using TGRA","authors":"Quang-Phuoc Tran, T. Le, Shyh-Chour Huang","doi":"10.1109/ECICE50847.2020.9301991","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9301991","url":null,"abstract":"This study aims to prove the influence of wetness on the mechanical characteristic of carbon fiber–reinforced plastic (CFRP). There is no suitable method for using lubrication fluids in the composite industry. There is a significant impact on CFRP machining capabilities by the geometry of the cutting tool and cryogenic liquid cooling. This paper selects the optimal parametric combinations of the carbon fiber reinforced plastic drilling process by using Taguchi optimization technique base on grey relation analysis (GRA) technique (TGRA). The parameters of the drilling process such as the helical angle of the blade, the coolant gas, and the feed rate were found by observing multi-responses output such as surface roughness and diameter of the drill hole. The following parameters resulted in a larger value of grey relational grade (GRG) to reduce the surface roughness and the error deviation of the diameter dimension: the speed of the spindle motor was 6100 rpm, the feed rate was 1006 mm/min, the helical angle of the cutting blade was triple, the coolant gas was CO2-N2 mixture. Finally, an analysis of variance (ANOVA) is used to analyze the effect of each parameter process in the estimation of GRG. The results showed that the coolant gas had an outstanding effect on the surface roughness and error deviation of the diameter dimension.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132516533","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9301958
P. Gao, W. Rong, Tao Zou, Lefeng Wang, Lining Sun
The change of gray contract reflects the morphology of the sample in an SEM image. Quantifying the gray contract is important for flex manipulation and the vertical measurement with SEM. Traditional methods focus on the 2D plane, thus are limited by the complex experimental system and lack of timeliness. We design and fabricate a new microprobe that measures the vertical distance in SEM simply by processing images of the semi-transparent pinhole at the tip of the microprobe. First, we propose the model of the microprobe by watching the morphology of the AFM probe. Second, we obtain the structure parameters of the microprobe by analysis and simulation. Finally, we fabricate the microprobe that combines 3D printing and FIB precision manufacturing. The result provides the foundation for grayscale characterization experiments in the SEM.
{"title":"Design and Fabrication of Microprobe for Vertical Measurement using SEM","authors":"P. Gao, W. Rong, Tao Zou, Lefeng Wang, Lining Sun","doi":"10.1109/ECICE50847.2020.9301958","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9301958","url":null,"abstract":"The change of gray contract reflects the morphology of the sample in an SEM image. Quantifying the gray contract is important for flex manipulation and the vertical measurement with SEM. Traditional methods focus on the 2D plane, thus are limited by the complex experimental system and lack of timeliness. We design and fabricate a new microprobe that measures the vertical distance in SEM simply by processing images of the semi-transparent pinhole at the tip of the microprobe. First, we propose the model of the microprobe by watching the morphology of the AFM probe. Second, we obtain the structure parameters of the microprobe by analysis and simulation. Finally, we fabricate the microprobe that combines 3D printing and FIB precision manufacturing. The result provides the foundation for grayscale characterization experiments in the SEM.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132882543","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9302020
Xiaofan Sun, Qilong Ren, W. Hsu
Rapid urbanization has led to gradual water shortages and pollution which threaten securing water resources. Therefore, water resource has a key position in the development of society. Thus, the establishment of an index system for evaluating the capacity of water resources becomes important. In this study, a comprehensive analysis of relevant research results was performed to compile indexes for evaluating the capacity of water resources. The Delphi method was adopted to acquire expert opinions on the adequacy of various evaluation indexes. The interquartile range was used to assess the adequacy indexes. The study results serve as a reference for the evaluation of urban water resources.
{"title":"Framework for Evaluation Index System of Carrying Water Resource","authors":"Xiaofan Sun, Qilong Ren, W. Hsu","doi":"10.1109/ECICE50847.2020.9302020","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9302020","url":null,"abstract":"Rapid urbanization has led to gradual water shortages and pollution which threaten securing water resources. Therefore, water resource has a key position in the development of society. Thus, the establishment of an index system for evaluating the capacity of water resources becomes important. In this study, a comprehensive analysis of relevant research results was performed to compile indexes for evaluating the capacity of water resources. The Delphi method was adopted to acquire expert opinions on the adequacy of various evaluation indexes. The interquartile range was used to assess the adequacy indexes. The study results serve as a reference for the evaluation of urban water resources.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126795215","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9301919
Cheng-Yan Siao, Jhe-Wei Lin, Rong-Guey Chang
The applications of five-axis machining have been used widely recently. Owing to the expensive cost of machine tools, how to detect the collision in real time has become a critical issue. Indeed, in order to ensure that G-codes will not result in the collision, the developers may use some tools before the stage to process the five-axis machine tool on off line. Moreover, to reduce long execution time on off line, we propose a parallel method to remedy it in this paper. The objective of the proposed approach aims at improving the performance to detect collision in parallel by utilizing the functions of a GPU (Graphics Processing Unit).We address the issue above by inducing six separating axis in plan and 11 separating axis in non-plan for two triangle meshes. Then we propose a parallel approach by implementing a CUDA ( Compute Unified Device Architecture ) program based on a GPU. Finally, with our domain knowledge and experiences, we attempt to optimize the proposed work with loop unrolling and prefetching techniques to improve performance.. The result shows that our work is very efficiently by using the two techniques.
{"title":"A Fast Method to Detect Collision for Five-axis Machining with GPU","authors":"Cheng-Yan Siao, Jhe-Wei Lin, Rong-Guey Chang","doi":"10.1109/ECICE50847.2020.9301919","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9301919","url":null,"abstract":"The applications of five-axis machining have been used widely recently. Owing to the expensive cost of machine tools, how to detect the collision in real time has become a critical issue. Indeed, in order to ensure that G-codes will not result in the collision, the developers may use some tools before the stage to process the five-axis machine tool on off line. Moreover, to reduce long execution time on off line, we propose a parallel method to remedy it in this paper. The objective of the proposed approach aims at improving the performance to detect collision in parallel by utilizing the functions of a GPU (Graphics Processing Unit).We address the issue above by inducing six separating axis in plan and 11 separating axis in non-plan for two triangle meshes. Then we propose a parallel approach by implementing a CUDA ( Compute Unified Device Architecture ) program based on a GPU. Finally, with our domain knowledge and experiences, we attempt to optimize the proposed work with loop unrolling and prefetching techniques to improve performance.. The result shows that our work is very efficiently by using the two techniques.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123351689","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9302009
Po-Wei Huang, H. Peng, Y. Ke, Po-Chih Chen, Jun-Hao Mao
This study investigates the effects of the vent-area on bubble-microstructure and shrinkage variation of gas-assisted foam-injection molding (GAFIM). The molding material is polystyrene (PS), and the gas foaming agent is nitrogen (N2). This study carried out the injection experiment with and without GAFIM to observe the molding characteristics of gas-filling pressure variation. In addition, the integration of vent-area volumes and cavity pressure measurement was developed to achieve foam growth and microstructure inside the sample to observe the effect of with and without vent-area on shrinkage variation and correlated pressure distribution near gate position during the filling process. The experimental results revealed that with the vent-area, the sample dimension shrinkage was relatively improved and the sample weight was reduced. On the other hand, the bubble-distribution increased with the changes in the volume of the vent-area and gas-filling pressure as the foam growth space increased.
{"title":"Effect of Gas-assisted-foaming Mechanism and Vent-area Design on Bubble-microstructure and Shrinkage of Polystyrene Foam-Injection Molding","authors":"Po-Wei Huang, H. Peng, Y. Ke, Po-Chih Chen, Jun-Hao Mao","doi":"10.1109/ECICE50847.2020.9302009","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9302009","url":null,"abstract":"This study investigates the effects of the vent-area on bubble-microstructure and shrinkage variation of gas-assisted foam-injection molding (GAFIM). The molding material is polystyrene (PS), and the gas foaming agent is nitrogen (N2). This study carried out the injection experiment with and without GAFIM to observe the molding characteristics of gas-filling pressure variation. In addition, the integration of vent-area volumes and cavity pressure measurement was developed to achieve foam growth and microstructure inside the sample to observe the effect of with and without vent-area on shrinkage variation and correlated pressure distribution near gate position during the filling process. The experimental results revealed that with the vent-area, the sample dimension shrinkage was relatively improved and the sample weight was reduced. On the other hand, the bubble-distribution increased with the changes in the volume of the vent-area and gas-filling pressure as the foam growth space increased.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126386569","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9302024
Jen-Chieh Li, Shin-Jin Ho, Chung-Yang Sue
We proposed a design and sacrificial-based fabrication process of capacitive pressure sensor with SiGe as a structural layer and movable electrode. Simulated results showed that its sensitivity was around 15fF/bar in a full-scale span from 30 to 110kPa. The initial stress for the used materials was also discussed in this study. At a low deposition temperature of SiGe (<450°C), it is a promising and ideal candidate for post CMOS fabrication.
{"title":"Effects of Initial Stress on SiGe Capacitive Pressure Sensor","authors":"Jen-Chieh Li, Shin-Jin Ho, Chung-Yang Sue","doi":"10.1109/ECICE50847.2020.9302024","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9302024","url":null,"abstract":"We proposed a design and sacrificial-based fabrication process of capacitive pressure sensor with SiGe as a structural layer and movable electrode. Simulated results showed that its sensitivity was around 15fF/bar in a full-scale span from 30 to 110kPa. The initial stress for the used materials was also discussed in this study. At a low deposition temperature of SiGe (<450°C), it is a promising and ideal candidate for post CMOS fabrication.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121585064","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}
Pub Date : 2020-10-23DOI: 10.1109/ECICE50847.2020.9301952
Deeksha Gorige, Eyhab Al-Masri, Sergey Kanzhelev, H. Fattah
It is a common task when employing the microservices architecture to integrate a number of loosely coupled entities that communicate with each other resulting in service requests that disseminate through a number of service endpoints. As the number of service endpoints increases, identifying the path to which a service request passes through the network becomes a time consuming and challenging task. In addition, as part of service requests, personal data may be shared across a number of service providers without end-users’ knowledge. Hence, tracing service requests and the extent to which data is flowing from one service endpoint to another becomes inevitable. In this paper, we introduce a distributed tracing Privacy Risk Detection (dtPRD) framework for identifying potential privacy and security risks associated with the dissemination of data through the path a service request undergoes. Identifying any risks associated with data sharing across a service path or plan can help in classifying service endpoints that are vulnerable or have the potential of exposing data without the end user’s knowledge. Throughout the paper, we present experimental and validation results of our proposed approach which show the effectiveness and usefulness of the dtPRD framework.
{"title":"Privacy-Risk Detection in Microservices Composition Using Distributed Tracing","authors":"Deeksha Gorige, Eyhab Al-Masri, Sergey Kanzhelev, H. Fattah","doi":"10.1109/ECICE50847.2020.9301952","DOIUrl":"https://doi.org/10.1109/ECICE50847.2020.9301952","url":null,"abstract":"It is a common task when employing the microservices architecture to integrate a number of loosely coupled entities that communicate with each other resulting in service requests that disseminate through a number of service endpoints. As the number of service endpoints increases, identifying the path to which a service request passes through the network becomes a time consuming and challenging task. In addition, as part of service requests, personal data may be shared across a number of service providers without end-users’ knowledge. Hence, tracing service requests and the extent to which data is flowing from one service endpoint to another becomes inevitable. In this paper, we introduce a distributed tracing Privacy Risk Detection (dtPRD) framework for identifying potential privacy and security risks associated with the dissemination of data through the path a service request undergoes. Identifying any risks associated with data sharing across a service path or plan can help in classifying service endpoints that are vulnerable or have the potential of exposing data without the end user’s knowledge. Throughout the paper, we present experimental and validation results of our proposed approach which show the effectiveness and usefulness of the dtPRD framework.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122395981","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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