A collaborative architecture against DDOS attacks for cloud computing systems.

• Ano de defesa: 2018
• Autor(a) principal: Almeida, Thiago Rodrigues Meira de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Cloud computing; Computação em nuvem; DDOS; SDN; Security; Segurança de redes; SFC
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/3/3141/tde-25032019-114624/

Distributed attacks, such as Distributed Denial of Service (DDoS) ones, require not only the deployment of standalone security mechanisms responsible for monitoring a limited portion of the network, but also distributed mechanisms which are able to jointly detect and mitigate the attack before the complete exhaustion of network resources. This need led to the proposal of several collaborative security mechanisms, covering different phases of the attack mitigation: from its detection to the relief of the system after the attack subsides. It is expected that such mechanisms enable the collaboration among security nodes through the distributed enforcement of security policies, either by installing security rules (e.g., for packet filtering) and/or by provisioning new specialized security nodes on the network. Albeit promising, existing proposals that distribute security tasks among collaborative nodes usually do not consider an optimal allocation of computational resources. As a result, their operation may result in a poor Quality of Service for legitimate packet flows during the mitigation of a DDoS attack. Aiming to tackle this issue, this work proposes a collaborative solution against DDoS attacks with two main goals: (1) ensure an optimal use of resources already available in the attack\'s datapath in a proactive way, and (2) optimize the placement of security tasks among the collaborating security nodes. Regardless the characteristics of each main goal, legitimate traffic must be preserved as packet loss is reduced as much as possible.