Twitch Chat Fingerprinting

• The streaming content that we choose to watch canreveal much about our thoughts, opinions, and interests. Anadversary capable of determining what users watch thereforepresents a significant privacy threat. In this paper, we presentand evaluate the first fingerprinting attack on Twitch that allowsviewers of individual live streams to be identified despite thetraffic being encrypted. The attack targets the traffic patternsassociated with chat messages associated with each stream. Ourresults show that high accuracy can be achieved by eavesdroppingonly for a short time (e.g., 90 seconds) and that the accuracy canbe increased even further by interacting with the stream. We alsotake a closer look at how the accuracy and activity level differbetween different Twitch channels and provide insights into theaccuracy that attackers using different strategies for selectingtarget channels may have. Finally, we study countermeasures toprotect against such attacks and demonstrate that the naive use ofVPN is not enough. We instead present countermeasures alteringpacket timing and sizes. Our large-scale evaluation of differentcountermeasures provides important insights that help both thestreaming providers and users better protect their privacy.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Publication and Content Type

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