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AIMS Workshop - CAIDA, February 2016 The ICSI Haystack A Platform for Hybrid Mobile Measurements in the Wild Narseo Vallina-Rodriguez In collaboration with: S. Sundaresan, C. Kreibich, M. Allman, V. Paxson (ICSI/UC Berkeley) A.


  1. AIMS Workshop - CAIDA, February 2016 The ICSI Haystack A Platform for Hybrid Mobile 
 Measurements in the Wild Narseo Vallina-Rodriguez In collaboration with: S. Sundaresan, C. Kreibich, M. Allman, V. Paxson (ICSI/UC Berkeley) 
 A. Razaghpanah, P. Gill (Stony Brook University)

  2. How much do we know about the mobile ecosystem? 2

  3. The mobile jigsaw IPv6 LTE Privacy QUIC NAT CDNs Apps WiFi ACTIVE 
 Users MEASUREMENTS 3G MVNO Security Performance Proxies Ads DNS TLS CGNs 3

  4. The mobile jigsaw IPv6 LTE Privacy QUIC NAT CDNs Apps WiFi STATIC AND 
 DYNAMIC ANALYSIS Users 3G MVNO Security Performance Proxies Ads DNS TLS CGNs 4

  5. The mobile jigsaw IPv6 LTE Privacy QUIC NAT CDNs Apps WiFi INSTRUMENTED 
 PHONES 
 Users 3G MVNO (root access) Security Performance Proxies Ads DNS TLS CGNs 5

  6. The mobile jigsaw IPv6 LTE Privacy QUIC NAT CDNs Apps WiFi ISP 
 Users TRACES 3G MVNO Security Performance Proxies Ads DNS TLS CGNs 6

  7. The mobile jigsaw IPv6 LTE Privacy QUIC NAT CDNs Apps WiFi VPN AND 
 Users PROXY TRACES 3G MVNO Security Performance Proxies Ads DNS TLS CGNs 7

  8. TRADE- OFFS! 8

  9. The ideal mobile measurements platform: Real-world operation Comprehensiveness Local operation Large scale 9

  10. The ICSI Haystack A user-centric, and on-device measurements platform that intercepts and studies network traffic and app activity in user space 10

  11. 
 
 
 
 Max throughput: ~55 Mbps 
 Schematic view of Haystack Extra latency < 1-4 ms 
 Battery overhead: 2-9 % Contextualized 
 Anonymized 
 traffic analysis reports (IRB) Traffic Analyzer (off-path) Optional TLS 
 DB @ ICSI interception Java sockets! 😢 
 i.e., no-packet level traces TLS Forwarder 
 Proxy App traffic tun 
 Default 
 interface GW Raw 
 Internet packets

  12. A easy-to-deploy tool for mobile users! 12

  13. The user engagement challenge 13

  14. Technical details and performance evaluation: 14

  15. Ongoing and Future Research Directions 15

  16. We are [mostly] in the dark about how mobile apps behave in ANY network! “ I love working for the NSA, but if I’d wanted to snoop on people’s most intimate information, I’d have become an app developer! ” http://www.robcottingham.ca/

  17. Provides DPI and generates accurate behavioral signatures and how? Who do apps talk to, what do they talk about, New-generation analytics and ad networks use TLS! % of Apps Allows users to stay in control of their traffic 10 20 30 40 0 graph.facebook.com crashlytics.com google.com googleapis.com doubleclick.net flurry.com gstatic.com googlesyndication.com amazonaws.com scorecardresearch.com 17 googletagmanager.com amazon − adsystem.com mixpanel.com googleusercontent.com mopub.com google − analytics.com cloudfront.net twitter.com facebook.com twimg.com

  18. 
 
 Performance evaluation: Real-world DNS Median 𝞔 (t App -t tcpdump ) ( 𝞶 s) StdDev 𝞔 (t App -t tcpdump ) ( 𝞶 s) App JavaApp 1,254 658 Haystack 1,211 303 Can measure contextualized “ real-world ” traffic performance 
 Enables reactive measurements [ Allman+Paxson, PAM 2008 ] 18

  19. Community feedback: What are your reactions both as users and researchers? • How can we improve app usability and mobile transparency? • What are the most challenging, worrying and urging aspects 
 • of mobile systems? Visit: www.haystack.com 19

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