Pub Date : 2020-11-01DOI: 10.1109/SCC49832.2020.00037
Nitin Phuke, Saket Saurabh, M. Gharote, S. Lodha
Service organizations need to comply with numerous data regulations to protect and preserve their customers’ privacy. Any misuse of data and privacy breach can affect the organizations’ reputation and brand image. In service delivery scenarios, such as IT support help desk, agents need to access customer data to serve them effectively. This data often includes sensitive and personally identifiable information of the customer. While some amount of data exposure is needed to serve a customer, however, exposure to more data than required could be a threat to an individual’s privacy. Hence, organizations need to design methodologies to ensure customer privacy while achieving minimal cost of operations.In this paper, we propose the Privacy Enabled Task Allocation (PETA) model for assigning customer requests to agents so that the overall cost of operations and data exposure is minimal. Data exposure is minimized by restricting the amount of data exposure per agent and by regulating the assignment of tasks. The PETA problem is modelled as an integer linear program, which is NP-hard. To solve this combinatorial hard problem, we have designed an allocation algorithm based on the linear programming relaxation for finding a quick feasible solution.
{"title":"PETA: Privacy Enabled Task Allocation","authors":"Nitin Phuke, Saket Saurabh, M. Gharote, S. Lodha","doi":"10.1109/SCC49832.2020.00037","DOIUrl":"https://doi.org/10.1109/SCC49832.2020.00037","url":null,"abstract":"Service organizations need to comply with numerous data regulations to protect and preserve their customers’ privacy. Any misuse of data and privacy breach can affect the organizations’ reputation and brand image. In service delivery scenarios, such as IT support help desk, agents need to access customer data to serve them effectively. This data often includes sensitive and personally identifiable information of the customer. While some amount of data exposure is needed to serve a customer, however, exposure to more data than required could be a threat to an individual’s privacy. Hence, organizations need to design methodologies to ensure customer privacy while achieving minimal cost of operations.In this paper, we propose the Privacy Enabled Task Allocation (PETA) model for assigning customer requests to agents so that the overall cost of operations and data exposure is minimal. Data exposure is minimized by restricting the amount of data exposure per agent and by regulating the assignment of tasks. The PETA problem is modelled as an integer linear program, which is NP-hard. To solve this combinatorial hard problem, we have designed an allocation algorithm based on the linear programming relaxation for finding a quick feasible solution.","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115105444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/SCC49832.2020.00013
Andrei Palade, A. Mukhopadhyay, Aqeel H. Kazmi, Christian Cabrera, Evelyn Nomayo, Georgios Iosifidis, M. Ruffini, S. Clarke
Multi-access Edge Computing (MEC) provides cloud computing capabilities at the edge by offloading users’ service requests on MEC servers deployed at Base Stations (BS). Optimising the resource allocation on such distributed units in a physical area such as a city, especially for compute-intensive and latency-critical services, is a key challenge. We propose a swarm-based approach for placing functions in the edge using a serverless architecture, which does not require services to pre-occupy the required computing resources. The approach uses a probabilistic model to decide where to place the functions while considering the resources available at each MEC server and the latency between the physical servers and the application requester. A central controller with a federated view of available MEC servers orchestrates functions’ deployment and deals changes available resources. We compare our approach against the Best-Fit, Max-Fit, MultiOpt, ILP and Random baselines. Results show that our approach can reduce the latency of applications with limited effect on the resource utilisation.
{"title":"A Swarm-based Approach for Function Placement in Federated Edges","authors":"Andrei Palade, A. Mukhopadhyay, Aqeel H. Kazmi, Christian Cabrera, Evelyn Nomayo, Georgios Iosifidis, M. Ruffini, S. Clarke","doi":"10.1109/SCC49832.2020.00013","DOIUrl":"https://doi.org/10.1109/SCC49832.2020.00013","url":null,"abstract":"Multi-access Edge Computing (MEC) provides cloud computing capabilities at the edge by offloading users’ service requests on MEC servers deployed at Base Stations (BS). Optimising the resource allocation on such distributed units in a physical area such as a city, especially for compute-intensive and latency-critical services, is a key challenge. We propose a swarm-based approach for placing functions in the edge using a serverless architecture, which does not require services to pre-occupy the required computing resources. The approach uses a probabilistic model to decide where to place the functions while considering the resources available at each MEC server and the latency between the physical servers and the application requester. A central controller with a federated view of available MEC servers orchestrates functions’ deployment and deals changes available resources. We compare our approach against the Best-Fit, Max-Fit, MultiOpt, ILP and Random baselines. Results show that our approach can reduce the latency of applications with limited effect on the resource utilisation.","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116799584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/SCC49832.2020.00056
Christian Rondanini, B. Carminati, Federico Daidone, E. Ferrari
Nowadays, organizations need to set higher and higher business goals in order to cope with market requirements. Indeed, a widespread strategy for organizations is to join in inter-organizational processes, which set collaborations and resource sharing among involved organizations. However, the possible lack of trust among the organizations poses relevant issues on the processing of sensitive resources. A promising approach to cope with this issue is leveraging on blockchain technology. Thanks to its design and consensus algorithm, blockchain provides a trustworthy infrastructure that allows partners involved in the collaboration to monitor and perform audits on the workflow transitions. In general, the focus of the existing blockchain-based workflow management solutions is mainly workflow coordination. However, a challenging characteristic of some workflows is that they require the exchange of a big amount of data that has to be managed off-chain, that is, directly exchanged between data producer and consumer. This off-chain data sharing should be secured and controlled such to follow the workflow execution.To cope with this challenge, in this paper, we propose a controlled information sharing in inter-organizational workflows enforced via smart contracts. Smart contracts are designed to coordinate the workflow execution, as well as to deploy a set of authorizations granting access only to the task executor and only to those resources needed for task execution and only during the task activation. We have also run a set of experiments to show the feasibility of our approach.
{"title":"Blockchain-based controlled information sharing in inter-organizational workflows","authors":"Christian Rondanini, B. Carminati, Federico Daidone, E. Ferrari","doi":"10.1109/SCC49832.2020.00056","DOIUrl":"https://doi.org/10.1109/SCC49832.2020.00056","url":null,"abstract":"Nowadays, organizations need to set higher and higher business goals in order to cope with market requirements. Indeed, a widespread strategy for organizations is to join in inter-organizational processes, which set collaborations and resource sharing among involved organizations. However, the possible lack of trust among the organizations poses relevant issues on the processing of sensitive resources. A promising approach to cope with this issue is leveraging on blockchain technology. Thanks to its design and consensus algorithm, blockchain provides a trustworthy infrastructure that allows partners involved in the collaboration to monitor and perform audits on the workflow transitions. In general, the focus of the existing blockchain-based workflow management solutions is mainly workflow coordination. However, a challenging characteristic of some workflows is that they require the exchange of a big amount of data that has to be managed off-chain, that is, directly exchanged between data producer and consumer. This off-chain data sharing should be secured and controlled such to follow the workflow execution.To cope with this challenge, in this paper, we propose a controlled information sharing in inter-organizational workflows enforced via smart contracts. Smart contracts are designed to coordinate the workflow execution, as well as to deploy a set of authorizations granting access only to the task executor and only to those resources needed for task execution and only during the task activation. We have also run a set of experiments to show the feasibility of our approach.","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132965575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-19DOI: 10.1109/SCC49832.2020.00008
Samson Oni, Zhiyuan Chen, Adina Crainiceanu, K. Joshi, Don Needham
Organizations often need to share mission-dependent data in a secure and flexible way. Examples include contact tracing for a contagious disease such as COVID19, maritime search and rescue operations, or creating a collaborative bid for a contract. In such examples, the ability to access data may need to change dynamically, depending on the situation of a mission (e.g., whether a person tested positive for a disease, a ship is in distress, or a bid offer with given properties needs to be created). We present a novel framework to enable situation-aware access control in a federated Data-as-a-Service architecture by using semantic web technologies. Our framework allows distributed query rewriting and semantic reasoning that automatically adds situation based constraints to ensure that users can only see results that they are allowed to access. We have validated our framework by applying it to two dynamic use cases: maritime search and rescue operations and contact tracing for surveillance of a contagious disease. This paper details our implemented solution and experimental results of the two use cases. Our framework can be adopted by organizations that need to share sensitive data securely during dynamic, limited duration scenarios.
{"title":"A Framework for Situation-Aware Access Control in Federated Data-as-a-Service Systems Based on Query Rewriting","authors":"Samson Oni, Zhiyuan Chen, Adina Crainiceanu, K. Joshi, Don Needham","doi":"10.1109/SCC49832.2020.00008","DOIUrl":"https://doi.org/10.1109/SCC49832.2020.00008","url":null,"abstract":"Organizations often need to share mission-dependent data in a secure and flexible way. Examples include contact tracing for a contagious disease such as COVID19, maritime search and rescue operations, or creating a collaborative bid for a contract. In such examples, the ability to access data may need to change dynamically, depending on the situation of a mission (e.g., whether a person tested positive for a disease, a ship is in distress, or a bid offer with given properties needs to be created). We present a novel framework to enable situation-aware access control in a federated Data-as-a-Service architecture by using semantic web technologies. Our framework allows distributed query rewriting and semantic reasoning that automatically adds situation based constraints to ensure that users can only see results that they are allowed to access. We have validated our framework by applying it to two dynamic use cases: maritime search and rescue operations and contact tracing for surveillance of a contagious disease. This paper details our implemented solution and experimental results of the two use cases. Our framework can be adopted by organizations that need to share sensitive data securely during dynamic, limited duration scenarios.","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114868987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1109/scc49832.2020.00081
L. Herger, Rong-Fong Chang, M. Abe, Shubhi Asthana
{"title":"Symposium on Women in Services Computing Program","authors":"L. Herger, Rong-Fong Chang, M. Abe, Shubhi Asthana","doi":"10.1109/scc49832.2020.00081","DOIUrl":"https://doi.org/10.1109/scc49832.2020.00081","url":null,"abstract":"","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125247021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1109/scc49832.2020.00082
{"title":"SERVICES 2020 Program Committee","authors":"","doi":"10.1109/scc49832.2020.00082","DOIUrl":"https://doi.org/10.1109/scc49832.2020.00082","url":null,"abstract":"","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115657252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1109/scc49832.2020.00080
{"title":"Welcome Message from the SERVICES 2020 Women in Services Computing Symposium Chair","authors":"","doi":"10.1109/scc49832.2020.00080","DOIUrl":"https://doi.org/10.1109/scc49832.2020.00080","url":null,"abstract":"","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"120 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128488504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1109/scc49832.2020.00005
E. Bertino
This year’s Congress is in many ways different from the previous editions. Due to the current health crisis, in May 2020, after a careful evaluation, the organization committee of the IEEE SERVICES Congress 2020 made a very difficult but necessary decision to transform most of events of the IEEE SERIVCES Congress 2020 into an on-line format; the result is the on-line IEEE SERVICES Congress spanning the week of October 18-24, 2020. Only the opening ceremony of the IEEE SERVICES Congress 2020 takes place as an in-person one-day event on October 18 in Beijing, China. However, the on-line format and the Congress rescheduling from July to October have provided some nice opportunities. In addition to the initial deadline for paper submission (March 5, 2020), we were able to introduce a second deadline (June 5, 2020). These two deadlines combined with possibility for authors to resubmit revised versions of their papers have greatly enhanced the technical quality of the papers. Registration fees have also been greatly reduced and we hope that many of our colleagues in academia, industry and government will take advantage of these lower fees.
{"title":"Welcome Message from Congress 2020 General Chairs","authors":"E. Bertino","doi":"10.1109/scc49832.2020.00005","DOIUrl":"https://doi.org/10.1109/scc49832.2020.00005","url":null,"abstract":"This year’s Congress is in many ways different from the previous editions. Due to the current health crisis, in May 2020, after a careful evaluation, the organization committee of the IEEE SERVICES Congress 2020 made a very difficult but necessary decision to transform most of events of the IEEE SERIVCES Congress 2020 into an on-line format; the result is the on-line IEEE SERVICES Congress spanning the week of October 18-24, 2020. Only the opening ceremony of the IEEE SERVICES Congress 2020 takes place as an in-person one-day event on October 18 in Beijing, China. However, the on-line format and the Congress rescheduling from July to October have provided some nice opportunities. In addition to the initial deadline for paper submission (March 5, 2020), we were able to introduce a second deadline (June 5, 2020). These two deadlines combined with possibility for authors to resubmit revised versions of their papers have greatly enhanced the technical quality of the papers. Registration fees have also been greatly reduced and we hope that many of our colleagues in academia, industry and government will take advantage of these lower fees.","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130529835","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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