Medição, caracterização e redução dos custos associados ao tráfego de spam
| Ano de defesa: | 2016 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Universidade Federal de Minas Gerais
|
| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: | |
| Link de acesso: | https://hdl.handle.net/1843/ESBF-AE8R2C |
Resumo: | Spam messages are often used to propagate malware, to disseminate phishing exploits, and to advertise illegal products. Those messages generate costs for users and network operators, but it is hard to measure how much of their costs are associated with spam traffic, and who actually pays for it. In this work, we provide a method to quantify the transit costs of spam traffic. We issue traceroutes from RIPE Atlas vantage points to estimate the routes traversed by spam messages collected at five honeypots. These collectors simulate vulnerable machines and lead spammers to believe they are interacting with legitimate open relays and proxies. Then we map IP-level traceroute measurements to AS-level paths and use the database of inter-network business relationships to infer the spam traffic costs. Our results show that stub networks are systematically subject to high spam traffic costs and that large ASes can receive twice with the spam traffic of the same message. Furthermore, we show that some networks profit from spam traffic and might not be interested in filtering spam; other networks, even paying for spam traffic, when they can foward these messages to their customers may not be interested in filtering them. Finally, we present a simple but effective algorithm to identify the networks that would benefit in cooperating to filter spam traffic at the origin to reduce transit costs. |
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2019-08-11T03:14:38Z2025-09-09T00:19:42Z2019-08-11T03:14:38Z2016-03-28https://hdl.handle.net/1843/ESBF-AE8R2CSpam messages are often used to propagate malware, to disseminate phishing exploits, and to advertise illegal products. Those messages generate costs for users and network operators, but it is hard to measure how much of their costs are associated with spam traffic, and who actually pays for it. In this work, we provide a method to quantify the transit costs of spam traffic. We issue traceroutes from RIPE Atlas vantage points to estimate the routes traversed by spam messages collected at five honeypots. These collectors simulate vulnerable machines and lead spammers to believe they are interacting with legitimate open relays and proxies. Then we map IP-level traceroute measurements to AS-level paths and use the database of inter-network business relationships to infer the spam traffic costs. Our results show that stub networks are systematically subject to high spam traffic costs and that large ASes can receive twice with the spam traffic of the same message. Furthermore, we show that some networks profit from spam traffic and might not be interested in filtering spam; other networks, even paying for spam traffic, when they can foward these messages to their customers may not be interested in filtering them. Finally, we present a simple but effective algorithm to identify the networks that would benefit in cooperating to filter spam traffic at the origin to reduce transit costs.Universidade Federal de Minas GeraisSpamTécnicas de mediçãoTopologia de redeTelecomunicações Tráfego CustosSpam (Mensagens eletrônicas)ComputaçãoRedes de computadoresMedição, caracterização e redução dos custos associados ao tráfego de spaminfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisOsvaldo Luis Henriques de Morais Fonsecainfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGWagner Meira JuniorItalo Fernando Scota CunhaItalo Fernando Scota CunhaCristine HoepersDorgival Olavo Guedes NetoKlaus Steding-jessenMensagens de spam são utilizadas na propagação de malware, disseminação de phishing e na divulgação de produtos ilegais. Essas mensagens geram custos para usuários e operadores de rede, porém é difícil mensurar quanto desse custo está associado ao tráfego de spam e quem paga por esse tráfego. Neste trabalho, propusemos uma metodologia para quantificar o custo do tráfego de spam para os operadores de rede. Identificamos as rotas percorridas pelas mensagens de spam capturadas por cinco coletores. Combinando o volume do tráfego de spam, as rotas inferidas e a base de dados de relações entre ASes, mostramos que redes de borda são sistematicamente oneradas. Além disso, mostramos que algumas redes lucram com o tráfego de spam e provavelmente não estão interessadas em filtrar esse tráfego. Finalmente, apresentamos um algoritmo simples mas eficiente para identificar redes que se beneficiariam em cooperar na filtragem de spam para reduzir os custos associados ao tráfego de spam.UFMGORIGINALosvaldoluishenriquesfonseca.pdfapplication/pdf4174957https://repositorio.ufmg.br//bitstreams/2aed855f-2718-40ac-9fd5-d41751729e6f/downloadb88a27bdadf02e669f8b9e9cc78a4704MD51trueAnonymousREADTEXTosvaldoluishenriquesfonseca.pdf.txttext/plain104635https://repositorio.ufmg.br//bitstreams/84da98e5-a210-4de5-bc44-6ed4c42c61ce/download24b55d2e0bb9d8aa1b6885317655d910MD52falseAnonymousREAD1843/ESBF-AE8R2C2025-09-08 21:19:42.217open.accessoai:repositorio.ufmg.br:1843/ESBF-AE8R2Chttps://repositorio.ufmg.br/Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2025-09-09T00:19:42Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
| dc.title.none.fl_str_mv |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| title |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| spellingShingle |
Medição, caracterização e redução dos custos associados ao tráfego de spam Osvaldo Luis Henriques de Morais Fonseca Telecomunicações Tráfego Custos Spam (Mensagens eletrônicas) Computação Redes de computadores Spam Técnicas de medição Topologia de rede |
| title_short |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| title_full |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| title_fullStr |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| title_full_unstemmed |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| title_sort |
Medição, caracterização e redução dos custos associados ao tráfego de spam |
| author |
Osvaldo Luis Henriques de Morais Fonseca |
| author_facet |
Osvaldo Luis Henriques de Morais Fonseca |
| author_role |
author |
| dc.contributor.author.fl_str_mv |
Osvaldo Luis Henriques de Morais Fonseca |
| dc.subject.por.fl_str_mv |
Telecomunicações Tráfego Custos Spam (Mensagens eletrônicas) Computação Redes de computadores |
| topic |
Telecomunicações Tráfego Custos Spam (Mensagens eletrônicas) Computação Redes de computadores Spam Técnicas de medição Topologia de rede |
| dc.subject.other.none.fl_str_mv |
Spam Técnicas de medição Topologia de rede |
| description |
Spam messages are often used to propagate malware, to disseminate phishing exploits, and to advertise illegal products. Those messages generate costs for users and network operators, but it is hard to measure how much of their costs are associated with spam traffic, and who actually pays for it. In this work, we provide a method to quantify the transit costs of spam traffic. We issue traceroutes from RIPE Atlas vantage points to estimate the routes traversed by spam messages collected at five honeypots. These collectors simulate vulnerable machines and lead spammers to believe they are interacting with legitimate open relays and proxies. Then we map IP-level traceroute measurements to AS-level paths and use the database of inter-network business relationships to infer the spam traffic costs. Our results show that stub networks are systematically subject to high spam traffic costs and that large ASes can receive twice with the spam traffic of the same message. Furthermore, we show that some networks profit from spam traffic and might not be interested in filtering spam; other networks, even paying for spam traffic, when they can foward these messages to their customers may not be interested in filtering them. Finally, we present a simple but effective algorithm to identify the networks that would benefit in cooperating to filter spam traffic at the origin to reduce transit costs. |
| publishDate |
2016 |
| dc.date.issued.fl_str_mv |
2016-03-28 |
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2019-08-11T03:14:38Z 2025-09-09T00:19:42Z |
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2019-08-11T03:14:38Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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https://hdl.handle.net/1843/ESBF-AE8R2C |
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por |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Universidade Federal de Minas Gerais |
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Universidade Federal de Minas Gerais |
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