you_never_surf_alone
-
Upload
silvia-puglisi -
Category
Documents
-
view
76 -
download
2
Transcript of you_never_surf_alone
![Page 1: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/1.jpg)
YOU NEVER SURF ALONE. UBIQUITOUS TRACKING OFUSERS’ BROWSING HABITS.
Silvia Puglisi, David Rebollo-Monedero and Jordi Forné
Department of Telematics Engineering Universitat Politecnica de Catalunya
![Page 2: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/2.jpg)
AGENDABackgroundContributionModelling the user's footprintA metric of similarityExperimental resultsConclusions
![Page 3: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/3.jpg)
BACKGROUNDWhen users surf the web a network of personalisationservices tracks their preferences by following their browsinghabits.
These services combine information from different sources:
profiles and accounts that users create,browser cookies,device fingerprinting and so on.
![Page 4: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/4.jpg)
Online profiling often means collecting enough features todistinguish an individual among a group of candidates.
Knowing certain facts about an individual allows the addnetwork (or an attacker) to verify assumptions and makepredictions.
![Page 5: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/5.jpg)
CONTRIBUTIONS1. Introducing a model of the user online footprint.2. Introducing a measure of similarity between the user
profile and the observed advertising profile.3. Measuring how quickly a user is uniquely identified and
tracked by an advertising network.
![Page 6: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/6.jpg)
MODELLING THE USER’S FOOTPRINTWe model the user’s activity as series of events belonging toa certain identity.
Each event is a document containing different information.
Each document can be seen as a hypermedia document i.e.an object possibly containing graphics, audio, video, plaintext and hyperlinks.
We call the hyperlinks selectors and we use these to buildthe connections between documents.
![Page 7: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/7.jpg)
![Page 8: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/8.jpg)
We aggregate keywords each time the user creates a newevent by visiting a different url.
These keywords constitute the user profile of interests.
![Page 9: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/9.jpg)
With this model we assume that a particular category isweighted according to the number of times this has beencounted in the user profile.
We define the profile of a user um as the Probability MassFunction:
A histogram of relative frequencies of tags across the set oftag categories T.
![Page 10: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/10.jpg)
The profile of an ad is defined as the PMF:
Where q_{n,l} is the percentage of tags belonging to thecategory l which have been assigned to this specificadvertising item.
![Page 11: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/11.jpg)
A METRIC OF SIMILARITYWe consider the third party advertising network to operatelike a recommendation system suggesting products orservices based on the users' preferences.
We assume that the ad server suggest advertising based ona measure of similarity.
![Page 12: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/12.jpg)
We use the 1 − norm between the user and the advertistingprofile as a measurement of how the advertising network istracking the user profile:
![Page 13: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/13.jpg)
EXPERIMENTAL METHODOLOGY
![Page 14: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/14.jpg)
WHY WE CRAWLED TWITTER FEEDS
“https://blog.twitter.com/2014/introducing-the-website-tag-for-remarketing”
![Page 15: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/15.jpg)
EXPERIMENTAL RESULTS
![Page 16: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/16.jpg)
CONCLUSIONSWeb tracking happens very quickly in a few subsequentvisits to websites in a large advertising network.
Hypermedia models are able to capture both connectionsbetween entities as weel as individual events features andmetrics.
![Page 17: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/17.jpg)
FUTURE DEVELOPMENTWe would like to introduce a full set of metrics to measurethe distance between the advertising and the user's profile:
2-norm,KL-Divergence between the advertising profile and theobserved user profile,Fisher information.
![Page 18: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/18.jpg)
We are interested in measuring how social networks sharingbuttons and/or commenting services, included on websites,are able to track users even when these have not signed inwith their account.
We are interested to measure how Privacy EnhancingTechniques affect advertising networks.
![Page 19: you_never_surf_alone](https://reader031.fdocuments.net/reader031/viewer/2022030313/58acf89e1a28abca0c8b573f/html5/thumbnails/19.jpg)
"I do not want to live in a world where everything I do and say is recorded. That is not something I amwilling to support or live under."
Edward Snowden