Finish text for cache timing
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@ -735,7 +735,7 @@ caches, or imply a substantial change in user agent design.
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\citeauthor{feltenTimingAttacksWeb2000} \cite{feltenTimingAttacksWeb2000} were
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\citeauthor{feltenTimingAttacksWeb2000} \cite{feltenTimingAttacksWeb2000} were
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the first to conduct a study on the feasibility of cache timing attacks and
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the first to conduct a study on the feasibility of cache timing attacks and
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concluded that accuracy in determining whether a file has been loaded from cache
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concluded that accuracy in determining whether a file has been loaded from cache
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or downloaded from a server is generally very high ($>95\%$). Furthermore, they
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or downloaded from a server is generally very high ($>95$\%). Furthermore, they
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evaluated a host of countermeasures such as turning off caching, altering hit or
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evaluated a host of countermeasures such as turning off caching, altering hit or
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miss performance and turning off Java and JavaScript but concluded that they
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miss performance and turning off Java and JavaScript but concluded that they
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were unattractive or at worst ineffective. They propose a partial remedy for
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were unattractive or at worst ineffective. They propose a partial remedy for
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@ -753,12 +753,34 @@ tagging would effectively nullify the performance boost a \gls{CDN} provides by
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converting every cache hit into a cache miss. The authors themselves question
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converting every cache hit into a cache miss. The authors themselves question
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the effectiveness of such an approach.
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the effectiveness of such an approach.
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While the attack presented by \citeauthor{feltenTimingAttacksWeb2000} relies on
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Because the attack presented by \citeauthor{feltenTimingAttacksWeb2000} relies
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being able to accurately time resource loading, a reliable network is needed.
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on being able to accurately time resource loading, a reliable network is needed.
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Today a sizeable portion of internet activity comes from mobile devices which
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are often not connected via cable but wirelessly.
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\citeauthor{vangoethemClockStillTicking2015}
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\cite{vangoethemClockStillTicking2015} have therefore proposed four new methods
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to accurately time resource loading over unstable networks. By using these
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improved methods, they managed to determine whether a user is a member of a
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particular age group (in this case between 23 and 32). The authors also ran
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their attacks against other social networks (LinkedIn, Twitter, Google and
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Amazon), successfully extracting sensitive information on users. The research
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discussed so far has not tackled the problem through a quantitative perspective
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but instead focused on individual cases. Due to this missing piece,
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\citeauthor{sanchez-rolaBakingTimerPrivacyAnalysis2019}
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\cite{sanchez-rolaBakingTimerPrivacyAnalysis2019} conducted a survey on 10K
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websites to determine how feasible it is to perform a history sniffing attack on
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a large scale. Their tool \textsc{BakingTimer} collects timing information on
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\gls{HTTP} requests, checking for logged in status and sensitive data. Their
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results show that 71.07\% of the surveyed websites are vulnerable to the
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attack.
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\subsection{Cache Control Directives}
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\subsection{Cache Control Directives}
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\label{subsec:cache control directives}
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\label{subsec:cache control directives}
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Cache Control Directives can be supplied in the Cache-Control \gls{HTTP} header,
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allowing rules about storing, updating and deletion of resources in the cache to
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be defined.
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\subsection{DNS Cache}
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\subsection{DNS Cache}
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\label{subsec:dns cache}
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\label{subsec:dns cache}
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