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| Content Provider | ACM Digital Library |
|---|---|
| Author | van Dijk, Marten Devadas, Srinivas Fletcher, Christopher W. Ren, Ling Yu, Xiangyao |
| Abstract | Keeping user data private is a huge problem both in cloud computing and computation outsourcing. One paradigm to achieve data privacy is to use tamper-resistant processors, inside which users' private data is decrypted and computed upon. These processors need to interact with untrusted external memory. Even if we encrypt all data that leaves the trusted processor, however, the address sequence that goes off-chip may still leak information. To prevent this address leakage, the security community has proposed ORAM (Oblivious RAM). ORAM has mainly been explored in server/file settings which assume a vastly different computation model than secure processors. Not surprisingly, naïvely applying ORAM to a secure processor setting incurs large performance overheads. In this paper, a recent proposal called Path ORAM is studied. We demonstrate techniques to make Path ORAM practical in a secure processor setting. We introduce background eviction schemes to prevent Path ORAM failure and allow for a performance-driven design space exploration. We propose a concept called super blocks to further improve Path ORAM's performance, and also show an efficient integrity verification scheme for Path ORAM. With our optimizations, Path ORAM overhead drops by 41.8%, and SPEC benchmark execution time improves by 52.4% in relation to a baseline configuration. Our work can be used to improve the security level of previous secure processors. |
| Starting Page | 571 |
| Ending Page | 582 |
| Page Count | 12 |
| File Format | |
| ISSN | 01635964 |
| DOI | 10.1145/2508148.2485971 |
| Journal | ACM SIGARCH Computer Architecture News (CARN) |
| Volume Number | 41 |
| Issue Number | 3 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1981-04-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
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