Lune

NDSS2021顶会

OblivSketch: Oblivious Network Measurement as a Cloud Service

Shangqi Lai, Xingliang Yuan, Joseph K. Liu, Xun Yi, Qi Li, Dongxi Liu, Surya Nepal

出版方
2021年份
3顶会引用

摘要

—Network function virtualisation enables versatile network functions as cloud services with reduced cost. Specifically, network measurement tasks such as heavy-hitter detection and flow distribution estimation serve many core network functions for improved performance and security of enterprise networks. However, deploying network measurement services in third-party multi-tenant cloud service providers raises critical privacy and security concerns. Recent studies demonstrate that leaking and abusing flow statistics can lead to severe network attacks such as DDoS, network topology manipulation and poisoning, etc. In this paper, we propose OblivSketch, an oblivious network measurement service using Intel SGX. It employs hardware enclave for secure network statistics generation and queries. The statistics are maintained in newly designed oblivious data structures inside the SGX enclave and queried by data-oblivious algorithms to prevent data leakage caused by access patterns to the memory of SGX. To demonstrate the practicality, we implement OblivSketch as a full-fledge service integrated with the off-the-shelf SDN framework. The evaluations demonstrate that OblivSketch consumes a constant and small memory space (6MB) to track a massive amount of flows (from 30k to 1.45m), and it takes no more than 15ms to respond six widely adopted measurement queries for a 5s-trace with 70k flows.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper3

问问它们各自怎么用它

它引用的顶会 Paper24

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖