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丹尼尔·格鲁斯与斯特凡·加斯特_蜗牛负载互联网上的任何人都可以了解你在做什么.pdf

上传人: 张** 编号:175556 2024-09-13 82页 6.13MB

1、SnailLoadAnyone on the Internet Can Learn What Youre DoingStefan Gast,Daniel Gruss2024-08-07Graz University of Technology1Stefan Gast,Daniel GrussWho are we?Stefan GastPhD StudentGraz University of Technology notbobbytablesinfosec.exchange?notbobbytables?https:/stefangast.eu/Daniel GrussProfessorGra

2、z University of Technology lavadosinfosec.exchange?lavados?https:/gruss.cc/2Stefan Gast,Daniel GrussWho are we?Stefan GastPhD StudentGraz University of Technology notbobbytablesinfosec.exchange?notbobbytables?https:/stefangast.eu/Daniel GrussProfessorGraz University of Technology lavadosinfosec.exch

3、ange?lavados?https:/gruss.cc/2Stefan Gast,Daniel GrussSnailLoadWe can tell which website you visit,without running anything on your system:102030405060708090 100102030405060708090100PredictionWebsite010203040 503Stefan Gast,Daniel GrussWhat are Side Channels?4Stefan Gast,Daniel GrussWhat are Side Ch

4、annels?Obtain meta-data and derive data from it4Stefan Gast,Daniel GrussSide Channel Example5Stefan Gast,Daniel GrussTiming Side Channels6Stefan Gast,Daniel GrussLocal Timing Attack100200300400101104107Access time CPU cyclesNumber of accessesCache Hits Local code execution code to use secrets code t

5、o measure time code to exfiltrate data7Stefan Gast,Daniel GrussLocal Timing Attack100200300400101104107Access time CPU cyclesNumber of accessesCache HitsCache Misses Local code execution code to use secrets code to measure time code to exfiltrate data7Stefan Gast,Daniel GrussLocal Timing Attack10020

6、0300400101104107Access time CPU cyclesNumber of accessesCache HitsCache Misses Local code execution code to use secrets code to measure time code to exfiltrate data7Stefan Gast,Daniel GrussLocal Timing Attack100200300400101104107Access time CPU cyclesNumber of accessesCache HitsCache Misses Local co

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全文主要探讨了网络活动中的侧信道攻击,特别是一种名为“SnailLoad”的攻击,它通过监测网络延迟来识别用户观看的视频和网站。文章指出,即使是在高速网络环境下,由于网络拥塞和带宽限制,服务器端和客户端之间的数据传输速度也可能存在显著差异,这种差异可以被攻击者利用。研究显示,通过机器学习分析网络流量,可以精确地推断用户的行动,如观看的视频类型。文章还提到,这种攻击对网络隐私构成威胁,并指出谷歌和YouTube已经对相关问题进行了调查。最后,文章强调了网络连接可能泄露用户隐私的风险,并呼吁采取措施修复这一问题。
你的活动如何被远程知晓?" 如何泄露你的隐私?" 它是如何影响你的安全的?"
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