Estratégias para tratamento de ataques de negação de serviço na camada de aplicação em redes IP

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Dantas, Yuri Gil
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal da Paraíba
Brasil
Informática
Programa de Pós-Graduação em Informática
UFPB
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://repositorio.ufpb.br/jspui/handle/tede/7841
Resumo: Distributed Denial of Service (DDoS) attacks remain among the most dangerous and noticeable attacks on the Internet. Differently from previous attacks, many recent DDoS attacks have not been carried out over the Transport Layer, but over the Application Layer. The main difference is that in the latter, an attacker can target a particular application of the server, while leaving the others applications still available, thus generating less traffic and being harder to detected. Such attacks are possible by exploiting application layer protocols used by the target application. This work proposes a novel defense, called SeVen, for Application Layer DDoS attacks (ADDoS) based on the Adaptive Selective Verification (ASV) defense used for Transport Layer DDoS attacks. We used two approches to validate the SeVen: 1) Simulation: The entire defense mechanism was formalized in Maude tool and simulated using the statistical model checker (PVeStA). 2) Real scenario experiments: Analysis of efficiency SeVen, implemented in C++, in a real experiment on the network. We investigate the resilience for mitigating three attacks using the HTTP protocol: HTTPPOST, Slowloris, and HTTP-GET. The defence is effective, with high levels of availability, for all three types of attacks, despite having different attack profiles, and even for a relatively large number of attackers.