Flavio Cirillo, Bin Cheng, Raffaele Porcellana, Marco Russo, Gürkan Solmaz, Hisashi Sakamoto, S. Romano
{"title":"IntentKeeper:联邦数据分析面向意图的数据使用控制","authors":"Flavio Cirillo, Bin Cheng, Raffaele Porcellana, Marco Russo, Gürkan Solmaz, Hisashi Sakamoto, S. Romano","doi":"10.1109/LCN48667.2020.9314823","DOIUrl":null,"url":null,"abstract":"Data usage control is of utmost importance for federated data analytics across multiple business domains. However, the existing data usage control approaches are limited due to their complexity and inefficiency. This paper proposes an intent-oriented data usage control system for federated data analytics, called IntentKeeper. The system allows users to specify intents for data usage policies and services easily. Thus, it reduces the data sharing complexity for data providers and consumers. Moreover, IntentKeeper enforces preventive and proactive data usage control for better security and efficiency through joint decisions based on policy enforcement and service orchestration. The use case validations for the automotive industry scenario show that IntentKeeper significantly reduces the complexity of policy specification (up to 75% for moderately complex scenarios) compared to the state-of-the-art flow-based approach. Lastly, the experimental results show that the IntentKeeper system provides sufficiently short response times (less than 40ms) with minimal overhead (less than 10ms).","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"IntentKeeper: Intent-oriented Data Usage Control for Federated Data Analytics\",\"authors\":\"Flavio Cirillo, Bin Cheng, Raffaele Porcellana, Marco Russo, Gürkan Solmaz, Hisashi Sakamoto, S. Romano\",\"doi\":\"10.1109/LCN48667.2020.9314823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data usage control is of utmost importance for federated data analytics across multiple business domains. However, the existing data usage control approaches are limited due to their complexity and inefficiency. This paper proposes an intent-oriented data usage control system for federated data analytics, called IntentKeeper. The system allows users to specify intents for data usage policies and services easily. Thus, it reduces the data sharing complexity for data providers and consumers. Moreover, IntentKeeper enforces preventive and proactive data usage control for better security and efficiency through joint decisions based on policy enforcement and service orchestration. The use case validations for the automotive industry scenario show that IntentKeeper significantly reduces the complexity of policy specification (up to 75% for moderately complex scenarios) compared to the state-of-the-art flow-based approach. Lastly, the experimental results show that the IntentKeeper system provides sufficiently short response times (less than 40ms) with minimal overhead (less than 10ms).\",\"PeriodicalId\":245782,\"journal\":{\"name\":\"2020 IEEE 45th Conference on Local Computer Networks (LCN)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 45th Conference on Local Computer Networks (LCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LCN48667.2020.9314823\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LCN48667.2020.9314823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IntentKeeper: Intent-oriented Data Usage Control for Federated Data Analytics
Data usage control is of utmost importance for federated data analytics across multiple business domains. However, the existing data usage control approaches are limited due to their complexity and inefficiency. This paper proposes an intent-oriented data usage control system for federated data analytics, called IntentKeeper. The system allows users to specify intents for data usage policies and services easily. Thus, it reduces the data sharing complexity for data providers and consumers. Moreover, IntentKeeper enforces preventive and proactive data usage control for better security and efficiency through joint decisions based on policy enforcement and service orchestration. The use case validations for the automotive industry scenario show that IntentKeeper significantly reduces the complexity of policy specification (up to 75% for moderately complex scenarios) compared to the state-of-the-art flow-based approach. Lastly, the experimental results show that the IntentKeeper system provides sufficiently short response times (less than 40ms) with minimal overhead (less than 10ms).