{"title":"内部住宅IP代理:从大型测量活动中学到的经验教训","authors":"Elisa Chiapponi, M. Dacier, Olivier Thonnard","doi":"10.1109/EuroSPW59978.2023.00062","DOIUrl":null,"url":null,"abstract":"Residential IP Proxy (RESIP) providers represent a growing threat when used for web scraping and other malicious activities. RESIPs enable their customers to hide behind a vast network of residential IP addresses to perpetrate their actions. This helps the customers to evade detection. Thanks to two new large datasets of RESIP connections, we reveal new insights into RESIP inner functioning and modus operandi. We present the similarities and differences of the ecosystems associated with four RESIP providers (geographic distribution, types, management and amount of machines used). Moreover, we display how two of the providers have striking similarities and we propose a specific detection method to identify them. Furthermore, we show how to build a list of suspicious /24 blocks of IP addresses and use it to mitigate the actions of malicious parties behind RESIPs.","PeriodicalId":220415,"journal":{"name":"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Inside Residential IP Proxies: Lessons Learned from Large Measurement Campaigns\",\"authors\":\"Elisa Chiapponi, M. Dacier, Olivier Thonnard\",\"doi\":\"10.1109/EuroSPW59978.2023.00062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Residential IP Proxy (RESIP) providers represent a growing threat when used for web scraping and other malicious activities. RESIPs enable their customers to hide behind a vast network of residential IP addresses to perpetrate their actions. This helps the customers to evade detection. Thanks to two new large datasets of RESIP connections, we reveal new insights into RESIP inner functioning and modus operandi. We present the similarities and differences of the ecosystems associated with four RESIP providers (geographic distribution, types, management and amount of machines used). Moreover, we display how two of the providers have striking similarities and we propose a specific detection method to identify them. Furthermore, we show how to build a list of suspicious /24 blocks of IP addresses and use it to mitigate the actions of malicious parties behind RESIPs.\",\"PeriodicalId\":220415,\"journal\":{\"name\":\"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EuroSPW59978.2023.00062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EuroSPW59978.2023.00062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inside Residential IP Proxies: Lessons Learned from Large Measurement Campaigns
Residential IP Proxy (RESIP) providers represent a growing threat when used for web scraping and other malicious activities. RESIPs enable their customers to hide behind a vast network of residential IP addresses to perpetrate their actions. This helps the customers to evade detection. Thanks to two new large datasets of RESIP connections, we reveal new insights into RESIP inner functioning and modus operandi. We present the similarities and differences of the ecosystems associated with four RESIP providers (geographic distribution, types, management and amount of machines used). Moreover, we display how two of the providers have striking similarities and we propose a specific detection method to identify them. Furthermore, we show how to build a list of suspicious /24 blocks of IP addresses and use it to mitigate the actions of malicious parties behind RESIPs.