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Chipping Away at Censorship with User-Generated Content Sam Burnett, Nick Feamster and Santosh Vempala.

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Presentation on theme: "Chipping Away at Censorship with User-Generated Content Sam Burnett, Nick Feamster and Santosh Vempala."— Presentation transcript:

1 Chipping Away at Censorship with User-Generated Content Sam Burnett, Nick Feamster and Santosh Vempala

2 Internet Censorship is a Problem 12 censors 11 monitors 25% of population More on the way See for morehttp://rsf.org

3 It’s Not Only China…at Home, Too

4 Censored netUncensored net Bob Firewall Alice Intro to Internet Censorship Block Traffic Punish User Censor

5 Censored netUncensored net Bob Firewall Alice Solution: Use a Helper The helper sends messages to and from blocked hosts on your behalf Helper

6 Design Goals for the Helper Be robust against blocking Be deniable against user identification Require no dedicated infrastructure

7 What about Proxies and Mixnets? (e.g., Tor) Proxy Censored netUncensored net Bob Firewall Alice Censors can block proxies if the proxy list is public Not deniable if encryption is incriminating Requires dedicated infrastructure (network of proxies)

8 What About Covert Channels? (e.g., Infranet) Not entirely robust against blocking More deniable because messages are hidden Requires dedicated infrastructure (Web servers) Unblocked host usenix.org Censored netUncensored net Bob Firewall Alice

9 Collage: Let User-Generated Content Help Defeat Censorship Robust by using redundancy Users generate innocuous-looking traffic No dedicated infrastructure required User-generated content hosts Bob, a Flickr user

10 Why Might Collage Work? Lots of User-Generated Content (UGC) – More than 4 billion Flickr images – A day of video uploaded to YouTube every minute Many sites host UGC We have tools to store censored data in UGC – Steganography, watermarking

11 Outline Background and Design Goals Collage Design Performance and Demo

12 Content host Bob Collage, Step-by-Step Step 1: Obtain messageStep 3: Obtain cover media Your personal photos Generous users Step 4: Embed message in cover Next slide Step 5: Upload UGC to content hostStep 6: Find and download UGCStep 7: Decode message from UGCStep 2: Pick message identifier Application specific Only intended recipient should know it Vector Message Embedded Vector Alice Collage steps: 1.Obtain message 2.Pick message identifier 3.Obtain cover media 4.Embed message in cover 5.Upload UGC to content host 6.Find and download UGC 7.Decode message from UGC

13 Embedding Messages in Vectors Encrypt the message using the identifier Generate chunks using erasure coding – Generate many chunks, recover from any k-subset – Allows splitting among many vectors, robustness Embed chunks into vectors Steganography: hard to detect Watermarking: hard to remove Do the reverse to decode Collage steps: 1.Obtain message 2.Pick message identifier 3.Obtain cover media 4.Embed message in cover 5.Upload UGC to content host 6.Find and download UGC 7.Decode message from UGC

14 Where Are Bob’s Vectors? Crawling all of Flickr is not an option Must agree on a subset of a content host without any immediate communication Collage steps: 1.Obtain message 2.Pick message identifier 3.Obtain cover media 4.Embed message in cover 5.Upload UGC to content host 6.Find and download UGC 7.Decode message from UGC Solution: A predictable way of mapping message identifiers to subsets of content hosts

15 Message Identifier Solution: Task Mapping Tasks Receivers perform these tasks to get vectors Senders publish vectors so that when receivers perform tasks, they get the sender’s vectors Tasks 1.Hash the identifier 2.Hash the tasks 3.Map identifier to closest tasks Collage steps: 1.Obtain message 2.Pick message identifier 3.Obtain cover media 4.Embed message in cover 5.Upload UGC to content host 6.Find and download UGC 7.Decode message from UGC 1 1 Look at JohnDoe’s videos on YouTube Search for blue flowers on Flickr

16 How Does Collage Meet the Design Goals? Robust against blocking – Erasure coding – Many content hosts Deniable against user identification – Traffic only to/from content hosts – Depends upon task construction Require no dedicated infrastructure – Messages stored on content hosts

17 How Do You Start Using Collage? Send & Receive Messages 1.Distribute software – CDROM – Spam everyone – A secure network 2.Refresh task list – Receive using Collage – Online resource 3.Message identifier – Application specific Help Censored Users 1.Donate your UGC vectors – Photos on Flickr – Tweets on Twitter – Etc. 2.Write Collage applications

18 Outline Background and Design Goals Collage Design Performance and Demo

19 Performance Metrics Sender and receiver traffic overhead Sender and receiver transfer time Storage required on content hosts But these metrics can vary a lot: Different content hosts Different tasks Different applications

20 Case Study News ArticlesCovert Tweets Content hostFlickrTwitter Message size30 KB140 Bytes Vectors needed530 Storage needed600 KB4 KB Sending traffic1,200 KB1,100 KB Sending time5 minutes60 minutes Receiving traffic6,000 KB600 KB Receiving time2 minutes½ minute Experiments performed on a 768/128 Kbps DSL connection

21 Demo of a Collage Application

22 What Should You Do Now? Try out the demo application Donate your photos – For now, only Flickr Pro users – Embed news articles when you upload photos Visit

23 Conclusion Collage evades Internet censorship by tunneling messages inside user-generated content – Robust against blocking – Deniable against user identification – Requires no dedicated infrastructure More work needed – Statistical deniability against traffic analysis – Learn timing behavior from users – Tor bridge discovery

24

25 Yes, Steganography is Broken Doesn’t mean it isn’t still practical Collage can use new information hiding techniques as they come along – Not dependent upon a particular technology Use many hiding techniques in parallel

26 Can Bob Be Behind the Firewall?

27 Comparison to Other Systems TechniqueSystemRobustnessDeniabilityInfrastructure Onion routingTor Layered encryption; bridges Encryption Network of relay servers Anonymous r ingMixminion Many hops; mixing Encryption Network of r ers Covert channels Infranet Could use many proxy forwarders Browsing regular Web sites; Steganography Custom Web servers CovertFS Multiple content hosts Browsing regular Web sites; Steganography None Collage Erasure coding; Many content hosts Browsing content hosts; Info hiding None

28 “A Web based Covert File System”, HotOS ’07 Stores files inside of Flickr photos Intended for personal file storage Collage is more robust – Erasure coding – Automatically spread data among content hosts Could be implemented using Collage Implementation not publically available

29 Where Could We Store Content? Photo sharing sites (Wikipedia lists 71) Video sharing sites (Wikipedia lists 68) Web forums, blogs – Plugins for popular forum and blogging software

30 What If Senders and Receivers Disagree on Task Lists? Consistent hashing ensures some agreement Depends on number of tasks per identifier: – If identifier mapped to 2 tasks, can still communicate with 25% disagreement – If identifier mapped to 4 tasks, can still communicate with 50% disagreement

31 Agreeing on Message Identifiers Goal: Agree without communicating For news reader application: – Public knowledge, hopefully censor doesn’t block Another option: – Exchange keys with communicators beforehand – Identifier is, e.g., ciphertext of current date

32 What Affects Deniability? Task construction: – The content host – Popularity the sequence of Web requests made – Injection of think times – Injection of garbage requests – Alternative routes to the same vectors Frequency of task execution Are you uploading suspicious vectors? – E.g., tagging pictures with bogus terms

33 Censorship Is an Arms Race Popular systems will eventually be blocked We must continually create systems that are harder to compromise


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