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TREDIS – A Trusted Full-Fledged SGX-Enabled REDIS Solution

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Detalhes bibliográficos
Resumo:Currently, offloading storage and processing capacity to cloud servers is a growing trend among web-enabled services managing big datasets. This happens because high storage capacity and powerful processors are expensive, whilst cloud services provide cheaper, ongoing, elastic, and reliable solutions. The problem with this cloud-based out sourced solutions are that they are highly accessible through the Internet, which is good, but therefore can be considerably exposed to attacks, out of users’ control. By exploring subtle vulnerabilities present in cloud-enabled applications, management functions, op erating systems and hypervisors, an attacker may compromise the supported systems, thus compromising the privacy of sensitive user data hosted and managed in it. These attacks can be motivated by malicious purposes such as espionage, blackmail, identity theft, or harassment. A solution to this problem is processing data without exposing it to untrusted components, such as vulnerable OS components, which might be compromised by an attacker. In this thesis, we do a research on existent technologies capable of enabling appli cations to trusted environments, in order to adopt such approaches to our solution as a way to help deploy unmodified applications on top of Intel-SGX, with overheads com parable to applications designed to use this kind of technology, and also conducting an experimental evaluation to better understand how they impact our system. Thus, we present TREDIS - a Trusted Full-Fledged REDIS Key-Value Store solution, implemented as a full-fledged solution to be offered as a Trusted Cloud-enabled Platform as a Service, which includes the possibility to support a secure REDIS-cluster architecture supported by docker-virtualized services running in SGX-enabled instances, with operations run ning on always-encrypted in-memory datasets.
Autores principais:Reis, João Carlos Cristo
Assunto:Intel SGX REDIS Trusted Computing Trusted Execution Environments Data Protection Privacy-Preservation
Ano:2021
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:Currently, offloading storage and processing capacity to cloud servers is a growing trend among web-enabled services managing big datasets. This happens because high storage capacity and powerful processors are expensive, whilst cloud services provide cheaper, ongoing, elastic, and reliable solutions. The problem with this cloud-based out sourced solutions are that they are highly accessible through the Internet, which is good, but therefore can be considerably exposed to attacks, out of users’ control. By exploring subtle vulnerabilities present in cloud-enabled applications, management functions, op erating systems and hypervisors, an attacker may compromise the supported systems, thus compromising the privacy of sensitive user data hosted and managed in it. These attacks can be motivated by malicious purposes such as espionage, blackmail, identity theft, or harassment. A solution to this problem is processing data without exposing it to untrusted components, such as vulnerable OS components, which might be compromised by an attacker. In this thesis, we do a research on existent technologies capable of enabling appli cations to trusted environments, in order to adopt such approaches to our solution as a way to help deploy unmodified applications on top of Intel-SGX, with overheads com parable to applications designed to use this kind of technology, and also conducting an experimental evaluation to better understand how they impact our system. Thus, we present TREDIS - a Trusted Full-Fledged REDIS Key-Value Store solution, implemented as a full-fledged solution to be offered as a Trusted Cloud-enabled Platform as a Service, which includes the possibility to support a secure REDIS-cluster architecture supported by docker-virtualized services running in SGX-enabled instances, with operations run ning on always-encrypted in-memory datasets.