Pub Date : 2018-07-01DOI: 10.1109/SERVICES.2018.00024
Xing Min, Rongheng Lin
At present, the crime of telecom fraud, with advanced communications and Internet technologies, is growing rapidly and causing huge losses every year. The traditional fraud detection methods are less flexible. In this paper, we used the signaling data to train a clustering model, which can discover the hidden user characteristics of fraud phones. The paper puts forward the extraction method of behavior characteristics, reduce the dimension of features with principal component analysis and select the appropriate clustering parameters through grid search, then present the K-Means-based behavior identification system, which can help to distinguish the frauds and identify the fraud phone numbers. Finally, the feasibility of this model is verified by the actual sample dataset.
{"title":"K-Means Algorithm: Fraud Detection Based on Signaling Data","authors":"Xing Min, Rongheng Lin","doi":"10.1109/SERVICES.2018.00024","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00024","url":null,"abstract":"At present, the crime of telecom fraud, with advanced communications and Internet technologies, is growing rapidly and causing huge losses every year. The traditional fraud detection methods are less flexible. In this paper, we used the signaling data to train a clustering model, which can discover the hidden user characteristics of fraud phones. The paper puts forward the extraction method of behavior characteristics, reduce the dimension of features with principal component analysis and select the appropriate clustering parameters through grid search, then present the K-Means-based behavior identification system, which can help to distinguish the frauds and identify the fraud phone numbers. Finally, the feasibility of this model is verified by the actual sample dataset.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122902596","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 : 2018-07-01DOI: 10.1109/SERVICES.2018.00029
Robert Filepp, C. Adam, Milton Hernandez, M. Vukovic, Nikos Anerousis, Guanlai Zhang
IT compliance is an area of increasing attention and capital spend in enterprise IT environments. We present "Continuous Compliance", a framework that allows a managed IT services provider to automate the overall process of keeping IT assets conformant with enterprise policies, regulatory frameworks, and other best practices. Our framework applies to all cloud layers and service models: Infrastructure-, Platform-, and Software-as-a-Service. We describe our framework design, its operation, and the post-process analytics and reporting. We also examine remediation reports gathered from over 2,000 servers for a seven month period, graph the incidence of repeated remediations, and explore some reasons for gradually subsiding remediations.
{"title":"Continuous Compliance: Experiences, Challenges, and Opportunities","authors":"Robert Filepp, C. Adam, Milton Hernandez, M. Vukovic, Nikos Anerousis, Guanlai Zhang","doi":"10.1109/SERVICES.2018.00029","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00029","url":null,"abstract":"IT compliance is an area of increasing attention and capital spend in enterprise IT environments. We present \"Continuous Compliance\", a framework that allows a managed IT services provider to automate the overall process of keeping IT assets conformant with enterprise policies, regulatory frameworks, and other best practices. Our framework applies to all cloud layers and service models: Infrastructure-, Platform-, and Software-as-a-Service. We describe our framework design, its operation, and the post-process analytics and reporting. We also examine remediation reports gathered from over 2,000 servers for a seven month period, graph the incidence of repeated remediations, and explore some reasons for gradually subsiding remediations.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125424977","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 : 2018-07-01DOI: 10.1109/SERVICES.2018.00016
Amro Al-Said Ahmad, Péter András
Measuring and testing the performance of cloud-based software services is critically important in the context of rapid growth of cloud computing. Scalability, elasticity and efficiency are interrelated aspects of performance of cloud-based software services. Here we present a work that is focused on measuring the scalability of cloud-based software services in technical terms. We introduce technical scalability metrics inspired by earlier technical metrics of elasticity.
{"title":"Measuring the Scalability of Cloud-Based Software Services","authors":"Amro Al-Said Ahmad, Péter András","doi":"10.1109/SERVICES.2018.00016","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00016","url":null,"abstract":"Measuring and testing the performance of cloud-based software services is critically important in the context of rapid growth of cloud computing. Scalability, elasticity and efficiency are interrelated aspects of performance of cloud-based software services. Here we present a work that is focused on measuring the scalability of cloud-based software services in technical terms. We introduce technical scalability metrics inspired by earlier technical metrics of elasticity.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114263135","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 : 2018-07-01DOI: 10.1109/services.2018.00008
{"title":"IEEE Services 2018 Review Panel","authors":"","doi":"10.1109/services.2018.00008","DOIUrl":"https://doi.org/10.1109/services.2018.00008","url":null,"abstract":"","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134283689","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 : 2018-07-01DOI: 10.1109/SERVICES.2018.00043
Michael Bardwell, Jason Wong, Steven Zhang, P. Musílek
A real-time solar array monitoring model based on Internet of Things (IoT) connectivity and cloud computing is proposed. Live control of maximum power point tracking (MPPT) parameters is realized via decisions computed on the Amazon Web Services (AWS) cloud. Information from a community of connected houses can be used to identify potential rooftop shading patterns. It can also share instantaneous power data for algorithm adjustment, creating system redundancy. In this paper, the feasibility of cloud based perturbation control for MPPT is discussed; tests on two separate IoT development boards show a maximum frequency of around 70 Hz, with the communication time acting as over 90% of the bottleneck.
{"title":"Design Considerations for IoT-Based PV Charge Controllers","authors":"Michael Bardwell, Jason Wong, Steven Zhang, P. Musílek","doi":"10.1109/SERVICES.2018.00043","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00043","url":null,"abstract":"A real-time solar array monitoring model based on Internet of Things (IoT) connectivity and cloud computing is proposed. Live control of maximum power point tracking (MPPT) parameters is realized via decisions computed on the Amazon Web Services (AWS) cloud. Information from a community of connected houses can be used to identify potential rooftop shading patterns. It can also share instantaneous power data for algorithm adjustment, creating system redundancy. In this paper, the feasibility of cloud based perturbation control for MPPT is discussed; tests on two separate IoT development boards show a maximum frequency of around 70 Hz, with the communication time acting as over 90% of the bottleneck.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127405329","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 : 2018-07-01DOI: 10.1109/SERVICES.2018.00047
Meng Sun, Hao-peng Chen, Buqing Shu
With the unprecedented traffic demand from various mobile devices, bad quality of experience arises in traditional reactive networks, such as long loading time and frozen in the middle. This paper presents Predict-then-Prefetch caching strategy in 5G networks to improve the quality of experience. This strategy partitions the capacity of the base stations into the proactive cache to prefetch popular content for a sum total maximum of popularity and the reactive one to cache content which is unpopular or whose popularity can’t be forecast inaccurately. It is demonstrated that Predict-then-Prefetch caching strategy has the best proportion of the proactive cache with different percentages of time-related content. Under this best proportion of the circumstances where all content is time-related, this strategy improves hit ratio by 30% and reduces latency by 50% in the architecture of 200M small base stations, which could enhance the quality of experience to a great degree.
{"title":"Predict-then-Prefetch Caching Strategy to Enhance QoE in 5G Networks","authors":"Meng Sun, Hao-peng Chen, Buqing Shu","doi":"10.1109/SERVICES.2018.00047","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00047","url":null,"abstract":"With the unprecedented traffic demand from various mobile devices, bad quality of experience arises in traditional reactive networks, such as long loading time and frozen in the middle. This paper presents Predict-then-Prefetch caching strategy in 5G networks to improve the quality of experience. This strategy partitions the capacity of the base stations into the proactive cache to prefetch popular content for a sum total maximum of popularity and the reactive one to cache content which is unpopular or whose popularity can’t be forecast inaccurately. It is demonstrated that Predict-then-Prefetch caching strategy has the best proportion of the proactive cache with different percentages of time-related content. Under this best proportion of the circumstances where all content is time-related, this strategy improves hit ratio by 30% and reduces latency by 50% in the architecture of 200M small base stations, which could enhance the quality of experience to a great degree.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129838317","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 : 2018-07-01DOI: 10.1109/services.2018.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/services.2018.00003","DOIUrl":"https://doi.org/10.1109/services.2018.00003","url":null,"abstract":"","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122999232","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 : 2018-07-01DOI: 10.1109/SERVICES.2018.00030
Xuefeng Huang, Rongheng Lin
Speech classification methods mainly focus on the content of the voice segment. To help better underestand the information in a segmented voice, the contents of other segments in the same paragraph should also be paid attention to. In our custom service speech classification problem, we are facing a problem of classification a series of voice segments in a conversation separately into category "custom" or "custom service". Sometimes the voice of both parties in the same conversation can be both sound like a "custom service" or both sound like "custom". In order to make the right prediction, the model needs to know not only the content of the voice segment that it's classifying, but both parties' voice in a conversation, the extra information can help the model to determine who is "more likely" to be a custom service in a conversation. We propose a method called I-CNN, which combines the info-feed layer with CNN. The Info-feed layer allows the CNN to use information from other samples in the same batch, which is helpful in improving the model's performance in our custom service speech classification problem.
{"title":"An I-CNN Based Speech Classification Algorithm for Custom Service","authors":"Xuefeng Huang, Rongheng Lin","doi":"10.1109/SERVICES.2018.00030","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00030","url":null,"abstract":"Speech classification methods mainly focus on the content of the voice segment. To help better underestand the information in a segmented voice, the contents of other segments in the same paragraph should also be paid attention to. In our custom service speech classification problem, we are facing a problem of classification a series of voice segments in a conversation separately into category \"custom\" or \"custom service\". Sometimes the voice of both parties in the same conversation can be both sound like a \"custom service\" or both sound like \"custom\". In order to make the right prediction, the model needs to know not only the content of the voice segment that it's classifying, but both parties' voice in a conversation, the extra information can help the model to determine who is \"more likely\" to be a custom service in a conversation. We propose a method called I-CNN, which combines the info-feed layer with CNN. The Info-feed layer allows the CNN to use information from other samples in the same batch, which is helpful in improving the model's performance in our custom service speech classification problem.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133757959","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 : 2018-07-01DOI: 10.1109/SERVICES.2018.00046
Matteo Signorini, Wael Kanoun, R. D. Pietro
Anomaly detection tools play a role of paramount importance in protecting networks and systems from unforeseen attacks, usually by automatically recognizing and filtering out anomalous activities. In this paper we present ADvISE: the first Anomaly Detection tool for blockchaIn SystEms which leverages blockchain meta-data, named forks, in order to collect potentially malicious requests in the network/system while being resilient to eclipse attacks. ADvISE collects and analyzes malicious forks to build a threat database that enables detection and prevention of future attacks.
{"title":"ADvISE: Anomaly Detection tool for blockchaIn SystEms","authors":"Matteo Signorini, Wael Kanoun, R. D. Pietro","doi":"10.1109/SERVICES.2018.00046","DOIUrl":"https://doi.org/10.1109/SERVICES.2018.00046","url":null,"abstract":"Anomaly detection tools play a role of paramount importance in protecting networks and systems from unforeseen attacks, usually by automatically recognizing and filtering out anomalous activities. In this paper we present ADvISE: the first Anomaly Detection tool for blockchaIn SystEms which leverages blockchain meta-data, named forks, in order to collect potentially malicious requests in the network/system while being resilient to eclipse attacks. ADvISE collects and analyzes malicious forks to build a threat database that enables detection and prevention of future attacks.","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131279709","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 : 2018-07-01DOI: 10.1109/services.2018.00001
{"title":"[Title page i]","authors":"","doi":"10.1109/services.2018.00001","DOIUrl":"https://doi.org/10.1109/services.2018.00001","url":null,"abstract":"","PeriodicalId":130225,"journal":{"name":"2018 IEEE World Congress on Services (SERVICES)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122663148","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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