Mohamed Bouziane, Sophie Gire, François Monin, Laurent Nana
This work is motivated by the rapid increase of the number of attacks in computer networks and software engineering. In this paper we study identity snowball attacks and formally prove the correctness of suggested solutions to this type of attack (solutions that are based on the graph reachability reduction) using a proof assistant. We propose a model of an attack graph that captures technical informations about the calculation of reachability of the graph. The model has been implemented with the proof assistant PVS 6.0 (Prototype Verification System). It makes it possible to prove algorithms of reachability reduction such as Sparsest_cut.
{"title":"Formal proof of security algorithms based on reachability reduction","authors":"Mohamed Bouziane, Sophie Gire, François Monin, Laurent Nana","doi":"10.1145/3012071.3012085","DOIUrl":"https://doi.org/10.1145/3012071.3012085","url":null,"abstract":"This work is motivated by the rapid increase of the number of attacks in computer networks and software engineering. In this paper we study identity snowball attacks and formally prove the correctness of suggested solutions to this type of attack (solutions that are based on the graph reachability reduction) using a proof assistant. We propose a model of an attack graph that captures technical informations about the calculation of reachability of the graph. The model has been implemented with the proof assistant PVS 6.0 (Prototype Verification System). It makes it possible to prove algorithms of reachability reduction such as Sparsest_cut.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116831483","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}
This paper discusses an optimization model to select and therefore coordinate marketing channels for contacting customers in an omni channel setup. The model assigns the appropriate channel to the corresponding business process with respect to customer segmentation, business process and available channel capacity. In this pursuit, a short introduction explains the motivation and aligns the topic with existing research. The subsequent method introduces the core problem of how to implement different channels for different customer segments and business processes. An example solution calculations is used to highlight the structure of the optimization model. Finally, limitations are explicated.
{"title":"Modeling marketing effort in an omni channel world","authors":"Christopher Freitag","doi":"10.1145/3012071.3012095","DOIUrl":"https://doi.org/10.1145/3012071.3012095","url":null,"abstract":"This paper discusses an optimization model to select and therefore coordinate marketing channels for contacting customers in an omni channel setup. The model assigns the appropriate channel to the corresponding business process with respect to customer segmentation, business process and available channel capacity. In this pursuit, a short introduction explains the motivation and aligns the topic with existing research. The subsequent method introduces the core problem of how to implement different channels for different customer segments and business processes. An example solution calculations is used to highlight the structure of the optimization model. Finally, limitations are explicated.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127017376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) is an emerging architecture that seeks to interconnect all of the "things" we use on a daily basis. Whereas the Internet originated as a way to connect traditional computing devices in order to share information, IoT includes everything from automobiles to appliances to buildings. As networks and devices become more diverse and disparate in their communication methods and interfaces, traditional host-to host technologies such as Internet Protocol (IP) are challenged to provide the level of data exchange and security needed to operate in this new network paradigm. Named Data Networking (NDN) is a developing Internet architecture that can help implement the IoT paradigm in a more efficient and secure manner. This paper introduces the NDN architecture in comparison to the traditional IP-based architecture and discusses several security concepts pertaining to NDN that make this a powerful technology for implementing the Internet of Things.
{"title":"An overview of architectural and security considerations for named data networking (NDN)","authors":"David Freet, R. Agrawal","doi":"10.1145/3012071.3012092","DOIUrl":"https://doi.org/10.1145/3012071.3012092","url":null,"abstract":"The Internet of Things (IoT) is an emerging architecture that seeks to interconnect all of the \"things\" we use on a daily basis. Whereas the Internet originated as a way to connect traditional computing devices in order to share information, IoT includes everything from automobiles to appliances to buildings. As networks and devices become more diverse and disparate in their communication methods and interfaces, traditional host-to host technologies such as Internet Protocol (IP) are challenged to provide the level of data exchange and security needed to operate in this new network paradigm. Named Data Networking (NDN) is a developing Internet architecture that can help implement the IoT paradigm in a more efficient and secure manner. This paper introduces the NDN architecture in comparison to the traditional IP-based architecture and discusses several security concepts pertaining to NDN that make this a powerful technology for implementing the Internet of Things.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132662757","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}
Convergence has been quietly reshaping not just media consumption but also the way we interact with products and services. Read/write access through personal and ambient devices enables the creation of free-flowing, actor-defined experiences that connect physical and digital artifacts, people, and locations into information-based ecosystems that vastly exceed the boundaries of the media industry. All sorts of everyday activities, from traveling to education to healthcare, are affected. This paper details the ways convergence is conceptualized in media studies and within product and service realization; argues that while media studies offer more mature descriptive frameworks, design practices are ill served by them as they are descriptive and not generative frameworks; proposes a formulation of cross-channel experiences as an information-based design artifact and of cross-channel ecosystems design as a pragmatical, actionable approach for dealing with convergent experiences in everyday activities.
{"title":"The architecture of cross-channel ecosystems: from convergence to experience","authors":"A. Resmini, Flávia Lacerda","doi":"10.1145/3012071.3012087","DOIUrl":"https://doi.org/10.1145/3012071.3012087","url":null,"abstract":"Convergence has been quietly reshaping not just media consumption but also the way we interact with products and services. Read/write access through personal and ambient devices enables the creation of free-flowing, actor-defined experiences that connect physical and digital artifacts, people, and locations into information-based ecosystems that vastly exceed the boundaries of the media industry. All sorts of everyday activities, from traveling to education to healthcare, are affected. This paper details the ways convergence is conceptualized in media studies and within product and service realization; argues that while media studies offer more mature descriptive frameworks, design practices are ill served by them as they are descriptive and not generative frameworks; proposes a formulation of cross-channel experiences as an information-based design artifact and of cross-channel ecosystems design as a pragmatical, actionable approach for dealing with convergent experiences in everyday activities.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133800419","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}
Melkamu Beyene, P. Portier, Solomon Atnafu, S. Calabretto
Although, the syntactical and structural heterogeneities among inter-language linked open data (LOD) data sources bring many challenges, entity co-reference resolution in a multilingual linked open data (MLOD) setting is not well studied. In this research, a three phase approach is proposed. First, statistical relational learning (SRL) with factorization of three way tensor is used to compute structural similarity between entities. Second, textual data from the Web of documents is associated in order to increase our knowledge of entities. Through a latent Dirichlet allocation (LDA), entities' textual data is projected into a cross-lingual topic space. This cross-lingual topic space is used to find textual similarities between entities. Third, a belief aggregation strategy is used to combine the structural and textual similarity results into a global similarity score. We have shown by experiments that our algorithm out-performs state of the art approaches based on tensor decomposition for the task of entity co-reference resolution in a MLOD setting.
{"title":"Dataset linking in a multilingual linked open data context","authors":"Melkamu Beyene, P. Portier, Solomon Atnafu, S. Calabretto","doi":"10.1145/3012071.3012090","DOIUrl":"https://doi.org/10.1145/3012071.3012090","url":null,"abstract":"Although, the syntactical and structural heterogeneities among inter-language linked open data (LOD) data sources bring many challenges, entity co-reference resolution in a multilingual linked open data (MLOD) setting is not well studied. In this research, a three phase approach is proposed. First, statistical relational learning (SRL) with factorization of three way tensor is used to compute structural similarity between entities. Second, textual data from the Web of documents is associated in order to increase our knowledge of entities. Through a latent Dirichlet allocation (LDA), entities' textual data is projected into a cross-lingual topic space. This cross-lingual topic space is used to find textual similarities between entities. Third, a belief aggregation strategy is used to combine the structural and textual similarity results into a global similarity score. We have shown by experiments that our algorithm out-performs state of the art approaches based on tensor decomposition for the task of entity co-reference resolution in a MLOD setting.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124660538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The explosion and rapid embrace of Massively Multiplayer Online Role Playing Games (MMORPG) has provided players with unique, fully immersive three dimensional environments in which they can express themselves in a myriad of ways. Players can develop unique skill sets, share knowledge, explore and experiment with various identities and network with like-minded individuals. Evidence suggests however, that these opportunities are accompanied with a number of risks including addiction, desensitisation and threats to the privacy of personal information. This paper presents a novel Taxonomy of opportunities and risks in the specific context of Massively Multiplayer Online Role Playing Games.
{"title":"A novel taxonomy of opportunities and risks in massively multiplayer online role playing games","authors":"Benjamin Sanders, Jims Marchang","doi":"10.1145/3012071.3012094","DOIUrl":"https://doi.org/10.1145/3012071.3012094","url":null,"abstract":"The explosion and rapid embrace of Massively Multiplayer Online Role Playing Games (MMORPG) has provided players with unique, fully immersive three dimensional environments in which they can express themselves in a myriad of ways. Players can develop unique skill sets, share knowledge, explore and experiment with various identities and network with like-minded individuals. Evidence suggests however, that these opportunities are accompanied with a number of risks including addiction, desensitisation and threats to the privacy of personal information. This paper presents a novel Taxonomy of opportunities and risks in the specific context of Massively Multiplayer Online Role Playing Games.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130839570","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}
Socialization is an essential process for building any society in natural ecosystems. In recent years, effective socialization processes have been investigated also within digital ecosystems also in the perspective of common and self-adaptive languages that allowboth "biotic" (human) and "abiotic" (physical) entities to socialize. In this paper, we propose a socialization and language self-adaptation method for enabling effective communicative interaction amongdigital entities acting in a digital ecosystem. The proposed method relies on an adaptableand extensible grammatical formalism, named Digital Ecosystem Grammar (DEG), which allows digital entities, represented as a multi-agent system, to interpret the messages expressed by other entities by using interaction, learning and evolution actions.Moreover, a grammar learning algorithm is applied to provide the self-adaptation mechanisms that allow the digital environment to adapt the interaction languageaccording to new incoming messages.
{"title":"Socialization and language self-adaptation in digital ecosystems","authors":"Arianna D’ulizia, F. Ferri, P. Grifoni","doi":"10.1145/3012071.3012083","DOIUrl":"https://doi.org/10.1145/3012071.3012083","url":null,"abstract":"Socialization is an essential process for building any society in natural ecosystems. In recent years, effective socialization processes have been investigated also within digital ecosystems also in the perspective of common and self-adaptive languages that allowboth \"biotic\" (human) and \"abiotic\" (physical) entities to socialize. In this paper, we propose a socialization and language self-adaptation method for enabling effective communicative interaction amongdigital entities acting in a digital ecosystem. The proposed method relies on an adaptableand extensible grammatical formalism, named Digital Ecosystem Grammar (DEG), which allows digital entities, represented as a multi-agent system, to interpret the messages expressed by other entities by using interaction, learning and evolution actions.Moreover, a grammar learning algorithm is applied to provide the self-adaptation mechanisms that allow the digital environment to adapt the interaction languageaccording to new incoming messages.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128886273","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}
Edgard Costa Oliveira, Edison Ishikawa, T. H. Granja, M. V. D. A. Nunes, Lucas Hiroshi Hironouchi, Cristiano Costa de Souza, Rafael Batista Menegassi, Luciano Gois
This paper describes the experience of researching and teaching the conceptual and practical basis for the specification, modelling and design of an ontology-based news authoring environment for the Semantic Web, that takes into account the construction and use of an ontology of the Zika disease. Some CMSs are being adapted in order to receive semantic features, such as automatic generations of keywords, semantic annotation and tagging, content reviewing etc. We present here the infrastructure designed to foster research on semantic CMSs as well as semantic web technologies that can be integrated into an ontology-based news authoring environment.
{"title":"Designing an ontology-based Zika virus news authoring environment for the semantic web","authors":"Edgard Costa Oliveira, Edison Ishikawa, T. H. Granja, M. V. D. A. Nunes, Lucas Hiroshi Hironouchi, Cristiano Costa de Souza, Rafael Batista Menegassi, Luciano Gois","doi":"10.1145/3012071.3012093","DOIUrl":"https://doi.org/10.1145/3012071.3012093","url":null,"abstract":"This paper describes the experience of researching and teaching the conceptual and practical basis for the specification, modelling and design of an ontology-based news authoring environment for the Semantic Web, that takes into account the construction and use of an ontology of the Zika disease. Some CMSs are being adapted in order to receive semantic features, such as automatic generations of keywords, semantic annotation and tagging, content reviewing etc. We present here the infrastructure designed to foster research on semantic CMSs as well as semantic web technologies that can be integrated into an ontology-based news authoring environment.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"408 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134127669","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}
Francesco Di Mauro, Paolo Pasteris, M. Sapino, K. Candan, G. Dino, P. Rossetti
When making decisions impacting public utility and encouraging and/or enforcing behavioral rules, public administrators need to rely on data and knowledge supporting their choices, which can be used to better inform those citizens who will be affected by such decisions. Many open data repositories exist and can be accessed and used by both decision makers and citizens. Similarly, semantic tagging is now commonly used as a way to allow users provide their own knowledge to be associated to data. In this paper, we present a novel participatory system which allows traditional databases and semantic tagging modules coexist in the same knowledge base, and provides the users with query enrichment functionalities to enable ontology-based query expansion. We describe CroSSE, our CrowdSourced Semantic Enrichment query system architecture, define the enrichment specification language, and discuss a use case in which the proposed technology is being applied in a participatory e-government setting. The use case is in the context of our SmartGround EU funded project, in which a relational database platform is designed to collect data of interest concerning secondary raw materials from mines as well as municipality waste. CroSSE semantic enrichment architecture interacts with this platform to expand queries and results on the basis of users' domain knowledge.
{"title":"CrowdSourced semantic enrichment for participatory e-Government","authors":"Francesco Di Mauro, Paolo Pasteris, M. Sapino, K. Candan, G. Dino, P. Rossetti","doi":"10.1145/3012071.3012102","DOIUrl":"https://doi.org/10.1145/3012071.3012102","url":null,"abstract":"When making decisions impacting public utility and encouraging and/or enforcing behavioral rules, public administrators need to rely on data and knowledge supporting their choices, which can be used to better inform those citizens who will be affected by such decisions. Many open data repositories exist and can be accessed and used by both decision makers and citizens. Similarly, semantic tagging is now commonly used as a way to allow users provide their own knowledge to be associated to data. In this paper, we present a novel participatory system which allows traditional databases and semantic tagging modules coexist in the same knowledge base, and provides the users with query enrichment functionalities to enable ontology-based query expansion. We describe CroSSE, our CrowdSourced Semantic Enrichment query system architecture, define the enrichment specification language, and discuss a use case in which the proposed technology is being applied in a participatory e-government setting. The use case is in the context of our SmartGround EU funded project, in which a relational database platform is designed to collect data of interest concerning secondary raw materials from mines as well as municipality waste. CroSSE semantic enrichment architecture interacts with this platform to expand queries and results on the basis of users' domain knowledge.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127264054","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}
Twitter is one of the most popular microblogging social systems, which provides a set of distinctive posting services operating in real time. The flexibility of these services has attracted unethical individuals, so-called "spammers", aiming at spreading malicious, phishing, and misleading information. Unfortunately, the existence of spam results non-ignorable problems related to search and user's privacy. In the battle of fighting spam, various detection methods have been designed, which work by automating the detection process using the "features" concept combined with machine learning methods. However, the existing features are not effective enough to adapt spammers' tactics due to the ease of manipulation in the features. Also, the graph features are not suitable for Twitter based applications, though the high performance obtainable when applying such features. In this paper, beyond the simple statistical features such as number of hashtags and number of URLs, we examine the time property through advancing the design of some features used in the literature, and proposing new time based features. The new design of features is divided between robust advanced statistical features incorporating explicitly the time attribute, and behavioral features identifying any posting behavior pattern. The experimental results show that the new form of features is able to classify correctly the majority of spammers with an accuracy higher than 93% when using Random Forest learning algorithm, applied on a collected and annotated data-set. The results obtained outperform the accuracy of the state of the art features by about 6%, proving the significance of leveraging time in detecting spam accounts.
{"title":"Leveraging time for spammers detection on Twitter","authors":"Mahdi Washha, Aziz Qaroush, F. Sèdes","doi":"10.1145/3012071.3012078","DOIUrl":"https://doi.org/10.1145/3012071.3012078","url":null,"abstract":"Twitter is one of the most popular microblogging social systems, which provides a set of distinctive posting services operating in real time. The flexibility of these services has attracted unethical individuals, so-called \"spammers\", aiming at spreading malicious, phishing, and misleading information. Unfortunately, the existence of spam results non-ignorable problems related to search and user's privacy. In the battle of fighting spam, various detection methods have been designed, which work by automating the detection process using the \"features\" concept combined with machine learning methods. However, the existing features are not effective enough to adapt spammers' tactics due to the ease of manipulation in the features. Also, the graph features are not suitable for Twitter based applications, though the high performance obtainable when applying such features. In this paper, beyond the simple statistical features such as number of hashtags and number of URLs, we examine the time property through advancing the design of some features used in the literature, and proposing new time based features. The new design of features is divided between robust advanced statistical features incorporating explicitly the time attribute, and behavioral features identifying any posting behavior pattern. The experimental results show that the new form of features is able to classify correctly the majority of spammers with an accuracy higher than 93% when using Random Forest learning algorithm, applied on a collected and annotated data-set. The results obtained outperform the accuracy of the state of the art features by about 6%, proving the significance of leveraging time in detecting spam accounts.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133353835","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：