کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
450698 694133 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
TrackerDetector: A system to detect third-party trackers through machine learning
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
TrackerDetector: A system to detect third-party trackers through machine learning
چکیده انگلیسی

Privacy violation caused by third-party tracking has become a serious problem, and the most effective defense against it is blocking. However, as the core part of blocking, the blacklist is usually manually curated and is difficult to maintain. To make it easier to generate a blacklist and reduce human work, we propose an effective system with high accuracy, named TrackerDetector, to detect third-party trackers automatically. Intuitively, the behaviors of trackers and non-trackers are different, which leads to different JavaScript API sets being called. Thus, an incremental classifier is trained from JavaScript files crawled from a large number of websites to detect whether a website is a third-party tracker. High accuracy of 97.34% is obtained with our dataset and that of 93.56% is obtained within a 10-fold cross validation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Networks - Volume 91, 14 November 2015, Pages 164–173
نویسندگان
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