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Touching from a Distance. Website Fingerprinting Attacks and Defenses . In a nutshell …. Web page fingerprinting attack Dodges defences such as HTTPOS Randomized pipelining over Tor A d hoc defenses unsuccessful. RECOGNIZING WEB PAGES.
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Touching from a Distance Website Fingerprinting Attacks and Defenses
In a nutshell … • Web page fingerprinting attack • Dodges defences such as • HTTPOS • Randomized pipelining over Tor • Ad hoc defenses unsuccessful
RECOGNIZING WEB PAGES • Identify web pages with the help of Packet ordering • Order of incoming and outgoing packets reveals information about • The size of objects referenced in a page • The order in which the browser re- quests them.
RECOGNIZING WEB PAGES • Computes the similarity of packet traces generated when a browser loads a web page • Converts traces into strings • Uses a distance metric to compare them • Trains a supportvector machine using a kernelbased on editdistance
RECOGNIZING WEB SITES Hidden Markov Model • capture the link structure of the site • capture the probable paths that users will follow among the pages when visiting the site. • use page fingerprinting technique to classify the packet traces
RECOGNIZING WEB SITES • Forward algorithm • Probability of observed trace of packets being generated when loading pages from the target web site • Attacker can know if a sequence of a victim’s page loads are all from the same web site
CONCLUSIONS • Local or national governments can snoop on citizens • Traffic morphing, HTTPOSand randomized pipeliningimpose high costs • Do not offer the guarantee of being impregnable to attacks • Proposed web site classifier is able to infer user’s online activities.