{"title":"网络信息共享中的复原力调查:分类学与应用技术","authors":"Agnaldo de Souza Batista, Aldri L. dos Santos","doi":"10.1145/3659944","DOIUrl":null,"url":null,"abstract":"<p>Information sharing is vital in any communication network environment to enable network operating services take decisions based on the information collected by several deployed computing devices. The various networks that compose cyberspace, as Internet-of-Things (IoT) ecosystems, have significantly increased the need to constantly share information, which is often subject to disturbances. In this sense, the damage of anomalous operations boosted researches aimed at improving resilience to information sharing. Hence, in this survey, we present a systematization of knowledge about scientific efforts for achieving resilience to information sharing on networks. First, we introduce a taxonomy to organize the strategies applied to attain resilience to information sharing on networks, offering brief concepts about network anomalies and connectivity services. Then, we detail the taxonomy in the face of malicious threats, network disruptions, and performance issues, discussing the presented solutions. Next, we analyze the techniques existing in the literature to foster resilience to information exchanged on communication networks to verify their benefits and constraints. Throughout the text, we highlight and argue issues that restrain the use of these techniques during the design and runtime.</p>","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8000,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Survey on Resilience in Information Sharing on Networks: Taxonomy and Applied Techniques\",\"authors\":\"Agnaldo de Souza Batista, Aldri L. dos Santos\",\"doi\":\"10.1145/3659944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Information sharing is vital in any communication network environment to enable network operating services take decisions based on the information collected by several deployed computing devices. The various networks that compose cyberspace, as Internet-of-Things (IoT) ecosystems, have significantly increased the need to constantly share information, which is often subject to disturbances. In this sense, the damage of anomalous operations boosted researches aimed at improving resilience to information sharing. Hence, in this survey, we present a systematization of knowledge about scientific efforts for achieving resilience to information sharing on networks. First, we introduce a taxonomy to organize the strategies applied to attain resilience to information sharing on networks, offering brief concepts about network anomalies and connectivity services. Then, we detail the taxonomy in the face of malicious threats, network disruptions, and performance issues, discussing the presented solutions. Next, we analyze the techniques existing in the literature to foster resilience to information exchanged on communication networks to verify their benefits and constraints. Throughout the text, we highlight and argue issues that restrain the use of these techniques during the design and runtime.</p>\",\"PeriodicalId\":50926,\"journal\":{\"name\":\"ACM Computing Surveys\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":23.8000,\"publicationDate\":\"2024-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Computing Surveys\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3659944\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3659944","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
A Survey on Resilience in Information Sharing on Networks: Taxonomy and Applied Techniques
Information sharing is vital in any communication network environment to enable network operating services take decisions based on the information collected by several deployed computing devices. The various networks that compose cyberspace, as Internet-of-Things (IoT) ecosystems, have significantly increased the need to constantly share information, which is often subject to disturbances. In this sense, the damage of anomalous operations boosted researches aimed at improving resilience to information sharing. Hence, in this survey, we present a systematization of knowledge about scientific efforts for achieving resilience to information sharing on networks. First, we introduce a taxonomy to organize the strategies applied to attain resilience to information sharing on networks, offering brief concepts about network anomalies and connectivity services. Then, we detail the taxonomy in the face of malicious threats, network disruptions, and performance issues, discussing the presented solutions. Next, we analyze the techniques existing in the literature to foster resilience to information exchanged on communication networks to verify their benefits and constraints. Throughout the text, we highlight and argue issues that restrain the use of these techniques during the design and runtime.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.