Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.82
Yousra Javed, Mohamed Shehab
The ability to stay connected with friends online and share information, has accounted for the popularity of online social networking websites. However, the overwhelming task of access control policy management for information shared on these websites has resulted in various mental models of sharing with a false sense of privacy. The misalignment between a user's intended and actual privacy settings causes access control misconfigurations, raising the risk of unintentional privacy leaks. In this paper, we propose a scheme to extract the user's mental model of sharing, enhance this model using information learned from their existing policies, and enable them to compose misconfiguration free policies. We present the possible misconfiguration patterns based on which we scan the Facebook user's access control policies. We implemented a prototype Facebook application of our scheme and conducted a pilot study using Amazon Mechanical Turk. Our preliminary results show that the users' intended policies were significantly different than their actual policies. Our scheme was able to detect the misconfiguration patterns in album policies. However, the reduction in the number of misconfigurations after using our approach was not significant. Participants' perceptions of our proposed policy misconfiguration patterns and the usability of our scheme was positive.
{"title":"Access Control Policy Misconfiguration Detection in Online Social Networks","authors":"Yousra Javed, Mohamed Shehab","doi":"10.1109/SocialCom.2013.82","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.82","url":null,"abstract":"The ability to stay connected with friends online and share information, has accounted for the popularity of online social networking websites. However, the overwhelming task of access control policy management for information shared on these websites has resulted in various mental models of sharing with a false sense of privacy. The misalignment between a user's intended and actual privacy settings causes access control misconfigurations, raising the risk of unintentional privacy leaks. In this paper, we propose a scheme to extract the user's mental model of sharing, enhance this model using information learned from their existing policies, and enable them to compose misconfiguration free policies. We present the possible misconfiguration patterns based on which we scan the Facebook user's access control policies. We implemented a prototype Facebook application of our scheme and conducted a pilot study using Amazon Mechanical Turk. Our preliminary results show that the users' intended policies were significantly different than their actual policies. Our scheme was able to detect the misconfiguration patterns in album policies. However, the reduction in the number of misconfigurations after using our approach was not significant. Participants' perceptions of our proposed policy misconfiguration patterns and the usability of our scheme was positive.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"65 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132551406","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.88
V. Lalanne, M. Munier, A. Gabillon
Service Oriented Architectures (SOA) offer new opportunities for the interconnection of systems. However, for a company, opening its Information System to the "world" is not insignificant in terms of security. Whether to use available services or provide its own services, new technologies have introduced new vulnerabilities and therefore new risks. Our work aims to propose an approach for risk management which is based on the ISO/IEC 27005:2011 standard: we propose a development of this standard (by an extension of Annex D) so that it can fully take into account the type "service" as web services and cloud services. Indeed, a world of services is not limited to link interconnected systems, it is more a relationship between customer and supplier, where notions of trust, accountability, trace ability and governance are developed. Following this study we introduce a new security criterion, controllability, to ensure that a company keeps control of its information even if it uses such outsourced services.
{"title":"Information Security Risk Management in a World of Services","authors":"V. Lalanne, M. Munier, A. Gabillon","doi":"10.1109/SocialCom.2013.88","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.88","url":null,"abstract":"Service Oriented Architectures (SOA) offer new opportunities for the interconnection of systems. However, for a company, opening its Information System to the \"world\" is not insignificant in terms of security. Whether to use available services or provide its own services, new technologies have introduced new vulnerabilities and therefore new risks. Our work aims to propose an approach for risk management which is based on the ISO/IEC 27005:2011 standard: we propose a development of this standard (by an extension of Annex D) so that it can fully take into account the type \"service\" as web services and cloud services. Indeed, a world of services is not limited to link interconnected systems, it is more a relationship between customer and supplier, where notions of trust, accountability, trace ability and governance are developed. Following this study we introduce a new security criterion, controllability, to ensure that a company keeps control of its information even if it uses such outsourced services.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130006601","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.78
Owen Sacco, J. Breslin
Online Social Network platforms provide users to create sensitive personal information such as user profiles that can be shared with other users within their social graph. Whilst these sites provide users with generic privacy settings to control who can be granted access, these platforms assume that all users in a social graph share the same level of trust. Moreover, these platforms also assume that what is shared within the Social Network can be trusted. Therefore, Social Networks do not take into consideration the notion of trust whilst users share or consume information. In this work, we conduct a user study to analyse the trends of interactions amongst users. We also analyse in detail the user's perception of trust whilst interacting within Social Networks. The results from this user study will help us understand how trust values can be asserted for users, sources and content by using information from within Social Networks.
{"title":"\"I Like\" - Analysing Interactions within Social Networks to Assert the Trustworthiness of Users, Sources and Content","authors":"Owen Sacco, J. Breslin","doi":"10.1109/SocialCom.2013.78","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.78","url":null,"abstract":"Online Social Network platforms provide users to create sensitive personal information such as user profiles that can be shared with other users within their social graph. Whilst these sites provide users with generic privacy settings to control who can be granted access, these platforms assume that all users in a social graph share the same level of trust. Moreover, these platforms also assume that what is shared within the Social Network can be trusted. Therefore, Social Networks do not take into consideration the notion of trust whilst users share or consume information. In this work, we conduct a user study to analyse the trends of interactions amongst users. We also analyse in detail the user's perception of trust whilst interacting within Social Networks. The results from this user study will help us understand how trust values can be asserted for users, sources and content by using information from within Social Networks.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130776034","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.15
Delfina Malandrino, V. Scarano, Raffaele Spinelli
People on the Web are generating and disclosing an ever-increasing amounts of data, often without full awareness of who is recording what about them, and who is aggregating and linking pieces of data with context information, for a variety of purposes. Awareness can help users to be informed about what silently happens during their navigation while learning from disclosure of personal information may help to discriminate potential harmful activities from daily and regular activities that can be performed online. Our main objective is to study whether a highly customized tool can help users to learn the value of privacy from their behaviors and make informed decisions to reduce their degree of exposure. To this aim, we present an evaluation study to analyze general perceptions, attitudes, and beliefs about privacy online, and to explore the resultant behaviors for two different groups of participants from an academic environment. Results show that users from the ICT field (Information and Communication Technology) are less concerned than non-ICT ones (i.e., not technological-oriented students), and that skill and expertise can influence the perception of the risks as well as the corresponding behaviors. Finally, students with less expertise in the ICT field learned more than the others, by showing greater willingness to adopt technologies to protect their privacy online.
{"title":"How Increased Awareness Can Impact Attitudes and Behaviors toward Online Privacy Protection","authors":"Delfina Malandrino, V. Scarano, Raffaele Spinelli","doi":"10.1109/SocialCom.2013.15","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.15","url":null,"abstract":"People on the Web are generating and disclosing an ever-increasing amounts of data, often without full awareness of who is recording what about them, and who is aggregating and linking pieces of data with context information, for a variety of purposes. Awareness can help users to be informed about what silently happens during their navigation while learning from disclosure of personal information may help to discriminate potential harmful activities from daily and regular activities that can be performed online. Our main objective is to study whether a highly customized tool can help users to learn the value of privacy from their behaviors and make informed decisions to reduce their degree of exposure. To this aim, we present an evaluation study to analyze general perceptions, attitudes, and beliefs about privacy online, and to explore the resultant behaviors for two different groups of participants from an academic environment. Results show that users from the ICT field (Information and Communication Technology) are less concerned than non-ICT ones (i.e., not technological-oriented students), and that skill and expertise can influence the perception of the risks as well as the corresponding behaviors. Finally, students with less expertise in the ICT field learned more than the others, by showing greater willingness to adopt technologies to protect their privacy online.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"97 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133321335","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 : 2013-09-08DOI: 10.1109/SOCIALCOM.2013.45
Giacomo Inches, Morgan Harvey, F. Crestani
In this work we study the problem of Authorship Attribution for a novel set of documents, namely online chats. Although the problem of Authorship Attribution has been extensively investigated for different document types, from books to letters and from emails to blog posts, to the best of our knowledge this is the first study of Authorship Attribution for conversational documents (IRC chat logs) using statistical models. We experimentally demonstrate the unsuitability of the classical statistical models for conversational documents and propose a novel approach which is able to achieve a high accuracy rate (up to 95%) for hundreds of authors.
{"title":"Finding Participants in a Chat: Authorship Attribution for Conversational Documents","authors":"Giacomo Inches, Morgan Harvey, F. Crestani","doi":"10.1109/SOCIALCOM.2013.45","DOIUrl":"https://doi.org/10.1109/SOCIALCOM.2013.45","url":null,"abstract":"In this work we study the problem of Authorship Attribution for a novel set of documents, namely online chats. Although the problem of Authorship Attribution has been extensively investigated for different document types, from books to letters and from emails to blog posts, to the best of our knowledge this is the first study of Authorship Attribution for conversational documents (IRC chat logs) using statistical models. We experimentally demonstrate the unsuitability of the classical statistical models for conversational documents and propose a novel approach which is able to achieve a high accuracy rate (up to 95%) for hundreds of authors.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114500614","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.112
Shaun Lichter, T. Friesz, C. Griffin
We extend the results of Goyal and Joshi (S. Goyal and S. Joshi. Networks of collaboration in oligopoly. Games and Economic behavior, 43(1):57-85, 2003), who first considered the problem of collaboration networks of oligopolies and showed that under certain linear assumptions network collaboration produced a stable complete graph through selfish competition. We show with nonlinear cost functions and player payoff alteration that stable collaboration graphs with an arbitrary degree sequence can result. We also show a generalized non-linear extension for the result in the aforementioned paper in which the complete graph is stable. An example is provided in which the complete set of pair wise stable collaborations is computed for an oligopoly consisting of five firms.
{"title":"Impact of a Non-linear Pay-Off Function on Pairwise Stable Collaborative Oligopolies","authors":"Shaun Lichter, T. Friesz, C. Griffin","doi":"10.1109/SocialCom.2013.112","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.112","url":null,"abstract":"We extend the results of Goyal and Joshi (S. Goyal and S. Joshi. Networks of collaboration in oligopoly. Games and Economic behavior, 43(1):57-85, 2003), who first considered the problem of collaboration networks of oligopolies and showed that under certain linear assumptions network collaboration produced a stable complete graph through selfish competition. We show with nonlinear cost functions and player payoff alteration that stable collaboration graphs with an arbitrary degree sequence can result. We also show a generalized non-linear extension for the result in the aforementioned paper in which the complete graph is stable. An example is provided in which the complete set of pair wise stable collaborations is computed for an oligopoly consisting of five firms.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114969697","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.144
Hiroshi Itsuki, H. Matsubara, Kazuki Arita, Kazunari Omi
Exploration of voter opinions is important for policy making. While opinion polls have long played an important role in this process, big data analysis of social media, i.e. "social listening", is becoming important. This is because social listening involves the collection of a huge amount of data on opinions that are transmitted spontaneously by people in real time. The amount is so huge that the data needs to be aggregated and summarized. Graph theory is an effective way of aggregating into groups network structured data collected from social media such as Twitter. However, there are two challenges. One is to combine the groups, i.e. "communities", into clusters because the granularity of the community is too fine for understanding the big picture. The other is to distinguish insignificant clusters from those that contain relevant information. In this paper, we describe a method for community clustering that is based on kurtosis and duration in time series of each community.
{"title":"Effective Clusterization of Political Tweets Using Kurtosis and Community Duration","authors":"Hiroshi Itsuki, H. Matsubara, Kazuki Arita, Kazunari Omi","doi":"10.1109/SocialCom.2013.144","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.144","url":null,"abstract":"Exploration of voter opinions is important for policy making. While opinion polls have long played an important role in this process, big data analysis of social media, i.e. \"social listening\", is becoming important. This is because social listening involves the collection of a huge amount of data on opinions that are transmitted spontaneously by people in real time. The amount is so huge that the data needs to be aggregated and summarized. Graph theory is an effective way of aggregating into groups network structured data collected from social media such as Twitter. However, there are two challenges. One is to combine the groups, i.e. \"communities\", into clusters because the granularity of the community is too fine for understanding the big picture. The other is to distinguish insignificant clusters from those that contain relevant information. In this paper, we describe a method for community clustering that is based on kurtosis and duration in time series of each community.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116025747","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 : 2013-09-08DOI: 10.1109/SOCIALCOM.2013.114
H. Thille, M. Cojocaru, E. Thommes, Dominic Nelson, S. Greenhalgh
We examine a pricing game between firms that produce differentiated products and in which consumer preferences evolve in response to the market shares of the available products. One of the products is new and a subset of consumers (early adopters) have a relatively strong preference for it, while the remaining consumers are influenced by the relative market shares of the two products, being drawn to the product with the higher market share. We use a system of PDEs to specify the evolution of the preferences for the alternative goods. This system is nonlinear due to the influence of existing consumption choice on the distribution of preferences. The pricing game allows firms to react to the changing distribution of consumer preference. We find that allowing for the evolution of consumer preference in this way results in interesting dynamics for prices. In particular, price paths can be non-monotonic over time.
{"title":"A Dynamic Pricing Game in a Model of New Product Adoption with Social Influence","authors":"H. Thille, M. Cojocaru, E. Thommes, Dominic Nelson, S. Greenhalgh","doi":"10.1109/SOCIALCOM.2013.114","DOIUrl":"https://doi.org/10.1109/SOCIALCOM.2013.114","url":null,"abstract":"We examine a pricing game between firms that produce differentiated products and in which consumer preferences evolve in response to the market shares of the available products. One of the products is new and a subset of consumers (early adopters) have a relatively strong preference for it, while the remaining consumers are influenced by the relative market shares of the two products, being drawn to the product with the higher market share. We use a system of PDEs to specify the evolution of the preferences for the alternative goods. This system is nonlinear due to the influence of existing consumption choice on the distribution of preferences. The pricing game allows firms to react to the changing distribution of consumer preference. We find that allowing for the evolution of consumer preference in this way results in interesting dynamics for prices. In particular, price paths can be non-monotonic over time.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116367842","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.73
A. Morton
With the increasing ubiquity and power of technology for collecting, storing, processing and disseminating personal information, a model of privacy concern is required - richer than that provided by existing classifications based on general privacy concern, or measures of concern about organizations' information handling practices. The author has previously proposed a model of users' privacy concerns encompassing: a) general, or inherent, privacy concern, b) environmental influences, and c) organization- and technology-specific attributes. As part of the development of this model, this paper describes a pilot survey study using an online survey instrument (N = 353) and structural equation modeling, to develop a measure of inherent privacy concern: Dispositional Privacy Concern (DPC). Two constructs within DPC were extracted from the survey data: 1) Concern about the Privacy Behavior of Organizations and Governments (CPBOG), and 2) Desire for Privacy (DFP). The study found the two personality metatraits of the Big Five - Stability and Plasticity - were negatively related to CPBOG and DFP, respectively. In turn, CPBOG and DFP were found to be positively related to the Internet Users' Information Privacy Concerns (Malhotra et al., 2004). The paper concludes with a discussion of the study's identification of the CPBOG and DFP constructs, the influence of personality traits on privacy concern, and the implications of the study's findings for research of general privacy concern.
随着收集、存储、处理和传播个人信息的技术日益普及和强大，需要一种隐私关注模型——比现有的基于一般隐私关注的分类或对组织信息处理实践的关注度量提供的模型更丰富。作者之前提出了一个用户隐私关注的模型，包括:a)一般或固有的隐私关注，b)环境影响，以及c)组织和技术特定属性。作为该模型发展的一部分，本文描述了一项使用在线调查工具(N = 353)和结构方程模型的试点调查研究，以开发固有隐私关注的度量:性情隐私关注(DPC)。从调查数据中提取了DPC中的两个结构:1)关注组织和政府的隐私行为(CPBOG)， 2)隐私欲望(DFP)。研究发现，大五人格元特征中的稳定性和可塑性分别与CPBOG和DFP呈负相关。反过来，CPBOG和DFP与互联网用户的信息隐私关注呈正相关(Malhotra et al.， 2004)。文章最后讨论了本研究对CPBOG和DFP构式的识别、人格特质对隐私关注的影响，以及本研究结果对一般隐私关注研究的启示。
{"title":"Measuring Inherent Privacy Concern and Desire for Privacy - A Pilot Survey Study of an Instrument to Measure Dispositional Privacy Concern","authors":"A. Morton","doi":"10.1109/SocialCom.2013.73","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.73","url":null,"abstract":"With the increasing ubiquity and power of technology for collecting, storing, processing and disseminating personal information, a model of privacy concern is required - richer than that provided by existing classifications based on general privacy concern, or measures of concern about organizations' information handling practices. The author has previously proposed a model of users' privacy concerns encompassing: a) general, or inherent, privacy concern, b) environmental influences, and c) organization- and technology-specific attributes. As part of the development of this model, this paper describes a pilot survey study using an online survey instrument (N = 353) and structural equation modeling, to develop a measure of inherent privacy concern: Dispositional Privacy Concern (DPC). Two constructs within DPC were extracted from the survey data: 1) Concern about the Privacy Behavior of Organizations and Governments (CPBOG), and 2) Desire for Privacy (DFP). The study found the two personality metatraits of the Big Five - Stability and Plasticity - were negatively related to CPBOG and DFP, respectively. In turn, CPBOG and DFP were found to be positively related to the Internet Users' Information Privacy Concerns (Malhotra et al., 2004). The paper concludes with a discussion of the study's identification of the CPBOG and DFP constructs, the influence of personality traits on privacy concern, and the implications of the study's findings for research of general privacy concern.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128371314","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 : 2013-09-08DOI: 10.1109/SocialCom.2013.107
A. Montplaisir-Goncalves, Naser Ezzati-Jivan, Florian Wininger, M. Dagenais
In this paper, we propose the State History Tree, a disk-based data structure to manage large streaming interval data. The State History Tree provides an efficient way to store interval data on permanent storage with a logarithmic access time. The disk-based structure ensures that extremely large data sets can be accommodated. The State History Tree stores intervals in blocks on disk in a tree organization. Unlike other interval management data structures like R-Trees, our solution avoids re-balancing the nodes, speeding up the tree construction. The proposed method is implemented in Java, and evaluated using large data sets (up to one terabyte). Those data sets were obtained from the state intervals computed from system events traced with the LTTng kernel tracer. The evaluation results demonstrate the performance and efficiency of the method, as compared with other solutions to managing huge interval data sets.
{"title":"State History Tree: An Incremental Disk-Based Data Structure for Very Large Interval Data","authors":"A. Montplaisir-Goncalves, Naser Ezzati-Jivan, Florian Wininger, M. Dagenais","doi":"10.1109/SocialCom.2013.107","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.107","url":null,"abstract":"In this paper, we propose the State History Tree, a disk-based data structure to manage large streaming interval data. The State History Tree provides an efficient way to store interval data on permanent storage with a logarithmic access time. The disk-based structure ensures that extremely large data sets can be accommodated. The State History Tree stores intervals in blocks on disk in a tree organization. Unlike other interval management data structures like R-Trees, our solution avoids re-balancing the nodes, speeding up the tree construction. The proposed method is implemented in Java, and evaluated using large data sets (up to one terabyte). Those data sets were obtained from the state intervals computed from system events traced with the LTTng kernel tracer. The evaluation results demonstrate the performance and efficiency of the method, as compared with other solutions to managing huge interval data sets.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128438389","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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