Proceedings of the 3rd International Conference on Information Science and Systems最新文献

{"title":"Utilizing SDN to Deliver Maximum TCP Flow for Data Centers","authors":"Norah S. Bin Saeed, Mohammed J. F. Alenazi","doi":"10.1145/3388176.3388216","DOIUrl":"https://doi.org/10.1145/3388176.3388216","url":null,"abstract":"Data centers host tens of thousands of interconnected servers, and they need to move a vast amount of data from one server to another for mirroring and backup purposes. Many new network technologies have been used to provide high throughput for bulk transfers of data in data centers. One of the evolving structures is the software-defined network (SDN), which is a new network paradigm that eases network management by separating the control plane from the data plane. In this paper, we introduce a novel method of utilizing traditional TCP and SDN to deliver maximum flow throughput. We also discuss our evaluation of our new method, MaxFlowTCP, against StandardTCP, ParallelTCP, and MPTCP. The results show that MaxFlowTCP provides higher throughput for the tested topology. Compared to StandardTCP, MaxFlowTCP had 130% better throughput, and compared to ParallelTCP and MPTCP, it had an average of 40% more throughput.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"10 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133076602","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}

{"title":"Systematization of Digital Twins: Ontology and Conceptual Framework","authors":"L. Barth, Matthias Ehrat, Rainer Fuchs, Jens Haarmann","doi":"10.1145/3388176.3388209","DOIUrl":"https://doi.org/10.1145/3388176.3388209","url":null,"abstract":"The development and progress in information and communication technologies will transform traditional products into smart products and allow to offer novel smart services [1]. Herein, the digital twin (DT) concept is regarded as a key technology to create value with smart services [2]. Although the research and applications of DTs emerge continuously many concerns are to be scrutinized [3]. The lack of a shared conceptual framework for DTs with an unambiguous terminology [4] complicates cross-functional discussions. Therefore, a systematization of the main dimensions of DTs is proposed in the form of an ontology and a conceptual framework thereof derived. The research questions addressed in this paper are a) «Which dimensions are used to classify and structure DTs in academic literature?», b) «What are the fundamental differences or specifications within these dimensions?» and c) «How do these different specifications relate to each other?» The focus of the research is on the objective to find classification systematics that are a) representing the entire spectrum of DTs, b) universally valid in all DT related domains and c) applicable in research and practice. A systematic literature review on the relevant aspects of DTs was conducted and the findings iteratively advanced within workshop sessions with academic experts. DTs are considered as integrators of physical and digital worlds as well as internal and external value creation. Further, the creation of DTs requires per definition the use of digital data. Hence, the proposed ontology and conceptual framework for DTs include the following main dimensions to consider for every DT: Data resources, external value creation and internal value creation. The main subdimensions of the data resources are the data sources to obtain the data, the data categories and the data formats. The main subdimension of the external value creation are the attributes of the services as the basis of the value propositions, the level of smartness of the connected products and the actors on the different levels of the ecosystem. The main subdimensions of the internal value creation are the lifecycle phases of products, the product management levels and the different generations of both. The proposed ontology and conceptual framework support researchers and practitioners in positioning and structuring their intended DT activities and communicating them to internal and external stakeholders. The holistic view on the data resource dimension further allows to easily deduct the needed data for certain applications or deduct possible applications from already available data.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114736089","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}

{"title":"False Positive Detection in Sender Domain Authentication by DMARC Report Analysis","authors":"Kanako Konno, Naoya Kitagawa, N. Yamai","doi":"10.1145/3388176.3388217","DOIUrl":"https://doi.org/10.1145/3388176.3388217","url":null,"abstract":"The number of spoofed emails is increasing rapidly and become a serious problem, especially in business and e-commerce. Sender domain authentication is an effective countermeasure for spoofed e-mail. Although SPF, DKIM, and DMARC are famous sender domain authentication methods, these methods erroneously determine legitimate e-mails as malicious e-mails, such as forwarded messages. On the other hand, DMARC has a reporting function, which e-mail senders can receive DMARC reports that include SPF and DKIM authentication results, and the sender's domains, and so on. Generally, spam e-mails countermeasures are combined with three approaches: TCP/SMTP session monitoring, sender domain authentication, and contents filtering. Since sender domain authentication is usually processed before contents filtering, the occurrence of many false positives in sender domain authentication is a serious problem. In this paper, we propose a method to detect legitimate IP addresses by adapting X-means clustering to DMARC reports data in order to detect false positive deliveries in sender domain authentications. We apply actual DMARC reports data received from 28th September to 5th October 2019 to our approach. As a result, our method classified 254 to 480 IP addresses per day as legitimate addresses. As an evaluation, we confirmed that 2.8% to 11.1% of e-mails from legitimate IP addresses detected by our method were failed the combination of SPF or DKIM verification, and 36.9% to 62.7% of them were failed to DMARC authentication. From these results, we confirmed the proposed method can detect false positive deliveries caused by conventional sender domain authentication with high accuracy.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125457379","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}

{"title":"Bidirectional Database Synchronization to the Cloud Computing Platform","authors":"Danijel Filipović, Danijel Sokac, R. Picek","doi":"10.1145/3388176.3388204","DOIUrl":"https://doi.org/10.1145/3388176.3388204","url":null,"abstract":"Diversity of subsystems in the organization can lead towards bad business results. Many companies decide to patch their business system with multiple subsystems which are usually not interoperable. Along with that, organizations have the dilemma of deciding whether to implement best-of-breed or one vendor solution. There is no correct answer to the dilemma. The outcome of the dilemma depends on each organization individually based on their analysis and needs. This article analyzes how to overcome data inconsistency caused by patching the business system and presents an approach to the synchronization of different databases to the Cloud. Usage of database synchronization tools to unify data in the Cloud is practical for mature organizations which aim to establish data consistency. The goal of this article is to consider some tools for database synchronization and to choose one for the practical example considering the known constraints. In the approach, we used few different databases to verify its compliance with chosen synchronization tool. The approach is based on practical example where couple of databases are synchronized to the Cloud ensuring the data consistency and bidirectional data flow. The solution includes chosen tool and the recommendation on how to ensure flawless data integration in the Cloud. Tests of synchronization duration with chosen databases and row quantities are conducted and analyzed at the end of the article.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127241760","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}

{"title":"Resolving XACML Rule Conflicts using Artificial Intelligence","authors":"B. Stepien, A. Felty","doi":"10.1145/3388176.3388188","DOIUrl":"https://doi.org/10.1145/3388176.3388188","url":null,"abstract":"The XACML access control policy specification language provides a simple rule/policy combining algorithm that is invoked when a request is evaluated against a particular policy set, and the results of the policy decision point (PDP) include solutions with both \"permit\" and \"deny\" effects. In short, the combining algorithm allows the policy writer to specify which effect should prevail in case of such conflicts. This feature has long been considered as misleading, and a wide variety of research has been done in an attempt to extend it using supplementary language features or algorithms based on priority definitions. We propose a new algorithm that, instead of absolute priorities expressed as numbers, is based on relative priorities that do not use numerical scales. Two kinds of annotations need to be added to policies, one that says if the value of an attribute is sensitive and another that provides information that can be used to determine which attribute is most important in the case when several sensitive values are encountered during the processing of attribute values in a request. This information serves as input to our decision making mechanism, designed to respect the user-specified priorities as best as possible.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131531817","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}

{"title":"On Possible Electromagnetic Precursors to a Significant Earthquake (Mw = 7.0) Occurred in JiuZhaiGou (China) on 8 August 2017","authors":"Z. Qiu, Shan-shan Yong, Xin'an Wang","doi":"10.1145/3388176.3388202","DOIUrl":"https://doi.org/10.1145/3388176.3388202","url":null,"abstract":"This paper reports an attempt to use low-frequency electromagnetic data (ED) from the Multi-component Seismic Monitoring System (AETA) in the study of earthquake precursors in China. The data from 5 AETA stations deployed within 200 km of the epicenter have been analyzed in the search for possible precursors to a strong earthquake that occurred JiuZhaiGou, (China) on 8 August 2017, with magnitude Mw = 7.0 and focal depth = 20 km. By calculating the correlation between the electromagnetic signals of every 2 AETA stations, an attempt is made to extract relatively weak electromagnetic anomaly information from a strong interference background. The analysis is based on a new method of calculating correlation, called local correlation tracking (LCT) method. Comparing with the classical correlation method, the proposed method can better extract the weak difference of this kind of electromagnetic signal. The electromagnetic data of AETA was analyzed by LCT method. It was found that the correlation coefficient showed an abnormality within one week before the earthquake, which indicated that the weak anomaly in the electromagnetic signal was found. It is concluded that this may be the electromagnetic precursor anomaly signal caused by the significant earthquake, so we hope that this will be helpful to the study of earthquake prediction.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128930389","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}

{"title":"CDN-hosted Domain Detection with Supervised Machine Learning through DNS Records","authors":"Hailing Li, Longtao He, Hui Zhang, Kai Zhang, Xiaoqian Li, Chenghai He","doi":"10.1145/3388176.3388206","DOIUrl":"https://doi.org/10.1145/3388176.3388206","url":null,"abstract":"Content delivery network (CDN) has become a critical infrastructure in the Internet and DNS-based request routing mechanism is widely used in CDNs. The current methods of CDN detection mainly use information such as hostname keywords, keywords in HTTP error message, PTR records and the public posted IP ranges. However, the application scope of these methods is limited. Considering the fact that CDN-hosted sites show some characteristics during the domain name resolution process, a novel machine learning algorithm for CDN-hosted site detection is proposed in this paper and three categories of features related to IPs, domains and TTLs are extracted from the DNS records. Machine learning classifiers are trained on a labeled dataset and the experimental results show that the method can achieve good precision and F1 score. Based on the feature evaluation, the IP and TTL related features are found to be more useful.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130644215","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}

{"title":"Research on Parallel Data Currency Rule Algorithms","authors":"Xuliang Duan, Bing Guo, Yan Shen, Yuncheng Shen, Xiangqian Dong, Hong Zhang","doi":"10.1145/3388176.3388210","DOIUrl":"https://doi.org/10.1145/3388176.3388210","url":null,"abstract":"Data currency is a temporal reference of data, which is related to the value of data and affects the results of data analysis and mining. The currency rules that reflect the time series features of data can be used not only for data repairing, but also for data quality evaluation. However, with the rapid growth and dynamic update of data volume, both the forms and algorithms of basic currency rule are facing severe challenges in application. Therefore, based on the research on data currency repairing, we extended the basic currency rule form, and proposed rule extraction and incremental updating algorithms that can run in parallel on dynamic data set. The experimental results show that, compared with non-parallel methods, the efficiency of parallel algorithms is significantly improved.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133745191","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}

{"title":"Discovering Knowledge of ASD from CCC-2: Ensemble Learning Approach for Analysis of ASD","authors":"Hirokazu Shimauchi, Naotake Tsukidate, Kan Hishiyama, Manabu Oi, Y. Yoshimura, M. Kikuchi, C. Hasegawa","doi":"10.1145/3388176.3388192","DOIUrl":"https://doi.org/10.1145/3388176.3388192","url":null,"abstract":"In this paper, we constructed an ASD classifier by random forest with responses of CCC-2 and the diagnosis results obtained from ADOS. Further the importance of features in CCC-2 for the classification of ASD was analyzed. The hyperparameters of the random forest were adjusted on the training dataset with the cross-validation, and the generalization performance was evaluated on the test dataset. Since the sample size was not so large, we validated the effect of random shuffling for the classification performance with additional 4 shuffle pattern. The all constructed classifiers not only had a highly classification performance, but also the result was stable with respect to random shuffling. It is also remarkable result that two items, which related to pragmatic impairments, were consistently determined to be the first, second important feature respectively. The items that reflect these pragmatic impairments were emphasized over the I and J domains in CCC-2, which reflect the main behavioral characteristics of ASD. It shed light on new aspects of ASD assessment for children.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123688229","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}

{"title":"IoT as an Enabler for Successful CSR Practices: The Case of Spanish Firms","authors":"M. Mattera","doi":"10.1145/3388176.3388177","DOIUrl":"https://doi.org/10.1145/3388176.3388177","url":null,"abstract":"Firms have been increasing their efforts towards sustainable manufacturing and service provision from pollution prevention to integrated approaches. With Internet's expansion, the degree of possibilities has been broadened exponentially. Considering its recent implementation, there is still a lack of understanding regarding the role that technology, specifically Internet of Things (IoT), plays in the implementation of Corporate Social Responsibility (CSR) strategies. The present study provides insights on how firms could leverage on IoT technology to succeed in the implementation of their CSR policies and presents empirical tools being implemented by companies.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129703008","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}