SS
S.N. Stancu
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A Comparative Study of Privacy-Preserving Computation Techniques
Contrasting ORAM, MPC, TEEs, Structured Encryption, and Homomorphic Encryption
Outsourcing data to the cloud can pose serious security threats due to an attacker observing the data access patterns, even though data is encrypted. Ideally, confidentiality should not depend on the server being a trusted party. Oblivious Random Access Machines are tackling this problem by obfuscating data access patterns and ensuring obliviousness of the server towards the data. Thus, this paper studies the evolution of Oblivious Random Access Machines and highlights the steps taken so far to discover a more practical algorithm for hiding data access patterns on an un trusted server. In addition, other approaches for privacy-preserving computation, such as Homomorphic Encryption, Structured Encryption, Multi Party Computation and Trusted Execution Environments are discussed and contrasted to ORAM to assess the costs and benefits they come with, but also the trade-offs in security and usability.
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Outsourcing data to the cloud can pose serious security threats due to an attacker observing the data access patterns, even though data is encrypted. Ideally, confidentiality should not depend on the server being a trusted party. Oblivious Random Access Machines are tackling this problem by obfuscating data access patterns and ensuring obliviousness of the server towards the data. Thus, this paper studies the evolution of Oblivious Random Access Machines and highlights the steps taken so far to discover a more practical algorithm for hiding data access patterns on an un trusted server. In addition, other approaches for privacy-preserving computation, such as Homomorphic Encryption, Structured Encryption, Multi Party Computation and Trusted Execution Environments are discussed and contrasted to ORAM to assess the costs and benefits they come with, but also the trade-offs in security and usability.