How Would Oblivious Memory Boost Graph Analytics on Trusted Processors?
By: Jiping Yu , Xiaowei Zhu , Kun Chen and more
Potential Business Impact:
Keeps secrets safe during computer calculations.
Trusted processors provide a way to perform joint computations while preserving data privacy. To overcome the performance degradation caused by data-oblivious algorithms to prevent information leakage, we explore the benefits of oblivious memory (OM) integrated in processors, to which the accesses are unobservable by adversaries. We focus on graph analytics, an important application vulnerable to access-pattern attacks. With a co-design between storage structure and algorithms, our prototype system is 100x faster than baselines given an OM sized around the per-core cache which can be implemented on existing processors with negligible overhead. This gives insights into equipping trusted processors with OM.
Similar Papers
Optimal Oblivious Algorithms for Multi-way Joins
Databases
Keeps your private data secret when using online services.
Enabling Low-Cost Secure Computing on Untrusted In-Memory Architectures
Cryptography and Security
Keeps computer secrets safe during fast calculations.
Leveraging FPGAs for Homomorphic Matrix-Vector Multiplication in Oblivious Message Retrieval
Cryptography and Security
Hides who is talking to whom online.