How To Identify Traffic Differentiation On Cell Phone Networks!

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1 Identifying Traffic Differentiation on Cellular Data Networks Arash Molavi Kakhki, Abbas Razaghpanah, Rajesh Golani, David Choffnes, Phillipa Gill, Alan Mislove Northeastern University, Stony Brook University

2 Introduction Traffic differentiation selectively changing the performance of network traffic Reasons for differentiation: traffic engineering bandwidth management business reasons X kb/s ISP Network Y kb/s X = Y? Do certain types of network traffic receive better (or worse) performance? 2

engineering bandwidth management business reasons X kb/s ISP Network Y

3 Goals Reliably detect differentiation in cellular networks On any app traffic Without requiring root privileges or OS modifications with few assumptions about traffic characteristics or packet shaper implementations Our approach is the only known way to test differentiation from non-rooted mobile devices 3

assumptions about traffic characteristics or packet shaper implementations

4 Assumptions What triggers differentiation? We don t know. We assume that they might trigger on: IP addresses ports total number of connections payload signatures total bandwidth time of day This is consistent with online manuals for DPI boxes 4

total number of connections payload signatures total

5 Record & Replay 1- Record: App Client App Server 2- Replay: Client Replay server 5

6 Methodology Record target application traffic using meddle and tcpdump Parse pcap and create transcript of packets Replay traffic alternately, tunneled and untunneled Analyze throughput, RTT, jitter, packet loss Record: Avoid running TCPDUMP on users devices. Utilize Meddle (a VPN proxy over IPSec) to record network traffic. App VPN Tunnel Meddle App Server 6

throughput, RTT, jitter, packet loss Record: Avoid running TCPDUMP on users devices.

7 Methodology Record target application traffic using meddle and tcpdump Parse pcap and create transcript of packets Replay traffic alternately, tunneled and untunneled Analyze throughput, RTT, jitter, packet loss Parse: Create two objects, one for the client side and one for server side. Handle unrelated/noise traffic. Parser client server 7

Analyze throughput, RTT, jitter, packet loss Parse: Create two objects, one for the

8 Methodology Record target application traffic using meddle and tcpdump Parse pcap and create transcript of packets Replay traffic alternately, tunneled and untunneled Analyze throughput, RTT, jitter, packet loss Replay: replay the salient features of application traffic such that it will be subject to differentiation from middleboxes alternate tunneling and plaintext to control visibility for packet shapers VPN Tunnel Client 8 Packet Shaper Replay server

the salient features of application traffic such that it will be subject to differentiation from middleboxes

9 Methodology Record target application traffic using meddle and tcpdump Parse pcap and create transcript of packets Replay traffic alternately, tunneled and untunneled Analyze throughput, RTT, jitter, packet loss Analyze: quantify differentiation in term of throughput, round trip time, jitter, loss, Analyzer 9

and untunneled Analyze throughput, RTT, jitter, packet loss Analyze: quantify

10 Proof of concept Replay Analysis Cumulative transfer (MB/s) Time (s) Original Replay CDF NoVPN VPN NoVPN w/ differentiation Throughput (KB/sec) YouTube traffic recorded on Verizon 3% loss and 10ms delay Replay produces traffic nearly identical to the original traffic. Detect differentiation in a controlled environment 10

2 0 NoVPN VPN NoVPN w/ differentiation 0 500 1000 1500 2000 Throughput (KB/sec) YouTube traffic

11 Future work Create a mobile app to enable wider adoption of the test (in progress). Run on networks we know there is differentiation to validate our techniques. Allow users to record and replay custom traces (longer term). Create a Differentiation Watch website and blog to report the results for different networks and blog about newly detected differentiation. Source-spoofing to detect destination IP-based differentiation.

Allow users to record and replay custom traces (longer term).

12 Related work Previous work explored this problem for limited protocols and in limited environments. Switzerland Glasnost Us Applications Tested P2P P2P and video Any application Features Tested Packet manipulation Performance Both Desktop App Yes Browser plugin Yes Smartphone App No No Yes Other closely related work NetDiff, NetPolice, NANO 12

Switzerland Glasnost Us Applications Tested P2P P2P and video Any application Features

13 Thank you 13

Identifying Traffic Differentiation in Mobile Networks

Identifying Traffic Differentiation in Mobile Networks Arash Molavi Kakhki, Abbas Razaghpanah, Anke Li, Hyungjoon Koo, Rajesh Golani David Choffnes, Phillipa Gill, Alan Mislove Northeastern University,