1
A Mobile Path to Censorship Resistance and Privacy Yue Liu, David Bild, David Adrian, Gulshan Singh, Robert Dick, Dan Wallach, and Z. Morley Mao This work was supported, in part, by NSF under award TC-0964545. The Internet Opened content access and creation, Hierarchical. Easy to shut down, censor, and spy on. Can we create a blocking-, censorship-, and surveillance-resistant network that is practical for normal smartphone users? How would that work? The Alternative Commodity smartphones. App install. Peer-to-peer WiFi. Fully distributed architecture. What about delay, required adoption rate, and implications of human motion patterns? What about reliability in the presence of denial of service attacks, Sybil attacks, and spam/propaganda? 1am microblogging app released on campus. 0 24 48 72 96 120 144 168 192 Elapsed time in hours 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Delivery rate 10 20 30 40 50 60 70 80 90 0 1 2 3 4 5 6 7 km 0 1 2 3 4 5 6 7 8 km North 10 0 10 1 10 2 10 3 85% delivery rate 13 hour latency 0.3% adoption rate Contact heat map 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Ratio of removed resources 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Delivery rate Random nodes Targeted nodes Targeted locations Internet Works with most important half of participants disabled. Phone-to-phone contacts happen throughout campus. Twice the observed contact rate of prior user studies. Sybil attack: A single physical entity can pretend to be multiple participants, gaining unfair inuence at low cost. A B C D E [...] A [...] D [...] E [...] C [...] B [...] D [...] E [...] C [...] A [...] D [...] E [...] B [...] A [...] C [...] D [...] B [...] A [...] C [...] E [...] B A B C D E B: 19 A: 25 B: 18 A: 12 B: 17 A: 20 A: 31 B: 27 A B C D E A: 12 A: 25 A: 31 A: 20 B: 19 B: 18 B: 17 B: 27 A I B S2 S1 I A B M A S1 S2 Identities transmit and record signal strengths. Exchange observations. Nodes form internally consistent world views. Tested on HTC Magic smartphones with 11 users. Challenges: Can't change hardware. No trusted authorities. Participants move. Insight: Can determine true worldview without trusting any participant. 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 True Positive Rate (Sensitivity) False Positive Rate (1 - Specificity) Office I Office II Cafeteria Outdoor 0.9 0.92 0.94 0.96 0.98 1 0 0.02 0.04 0.06 0.08 0.1 Eliminates 91%-100% of Sybil identities, depending on environment. What about spam/propaganda in this fully decentralized network? No central authority. What can be done with local information? Use transitive rebroadcast graph instead of followers graph. Less disassortive and more clustered, like non-digital social networks. Use graph structure to nd spammers. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.2 0.4 0.6 0.8 1 True Positive Rate False Positive Rate 0.00002 0.00006 0.00014 0.00030 0.00060 0.00300

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Page 1: E [] A [] B [] D [] E A Mobile Path to Censorship ... · Easy to shut down, censor, and spy on. Can we create a blocking-, censorship-, and surveillance-resistant network that is

A M

obile

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Yue

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