Towards Realistic and ReproducibleWeb Crawl Measurements
Towards Realistic and ReproducibleWeb Crawl Measurements
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DOI：
10.1145/3442381.3450050
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发表时间：
2021-04
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通讯作者：
Jordan Jueckstock;Shaown Sarker;Peter Snyder;Aidan Beggs;P. Papadopoulos;Matteo Varvello;B. Livshits;A. Kapravelos
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作者：
Jordan Jueckstock;Shaown Sarker;Peter Snyder;Aidan Beggs;P. Papadopoulos;Matteo Varvello;B. Livshits;A. Kapravelos
准确的网络测量对于理解和改善在线安全和隐私至关重要。这样的测量隐含地假设自动抓取推广到典型的Web用户体验。但有证据表明，由于各种原因，当通过众所周知的测量端点或测量自动化框架时，Web的行为会有所不同。我们的工作改善了网络隐私和安全的状态，通过调查如何关键的测量不同时，使用天真的爬行工具默认值与小心尝试匹配“真实的”用户在Tranco的前25k个Web域。我们发现网络隐私和安全测量显著受Vantage位置和浏览器配置的影响。我们的结论是，除非研究人员确保他们的网络测量工具与真实的用户体验相匹配，否则研究界可能会系统地错过重要的信号。例如，我们发现仅浏览器配置就导致19%的已知广告和跟踪域发生变化，并改变了高达10%的不同JavaScript代码单元的加载频率。我们发现，网络的Vantage位置有类似的，但不那么戏剧性，对相同的网络指标的影响。为了确保可重复性，我们仔细记录了我们的方法，并发布了我们的代码和收集的数据。
Accurate web measurement is critical for understanding and improving security and privacy online. Such measurements implicitly assume that automated crawls generalize to typical web user experience. But anecdotal evidence suggests the web behaves differently when seen via well-known measurement endpoints or measurement automation frameworks, for various reasons. Our work improves the state of web privacy and security by investigating how key measurements differ when using naive crawling tool defaults vs. careful attempts to match “real” users across the Tranco top 25k web domains. We find web privacy and security measurements significantly affected by vantage point and browser configuration. We conclude that unless researchers ensure their web measurement tools match real world user experience, the research community is likely missing important signals systematically. For example, we find browser configuration alone causing shifts in 19% of known ad and tracking domains encountered and altering the loading frequency of up to 10% of distinct JavaScript code units executed. We find network vantage point having similar, though less dramatic, effects on the same web metrics. To ensure reproducibility, we carefully document our methodology and publish both our code and collected data.