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Differences between In- and Outbound Internet Backbone Traffic

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Title: Differences between In- and Outbound Internet Backbone Traffic


1
Differences between In- and Outbound Internet
Backbone Traffic
  • Wolfgang John and Sven TafvelinDept. of Computer
    Science and EngineeringChalmers University of
    TechnologyGöteborg, Sweden

2
Overview
  • Introduction
  • Highlights of directional differences on
  • IP level
  • TCP level
  • UDP level
  • Summary of results
  • Conclusions

3
Introduction Motivation
  • Why measuring on Internet links?
  • to understand the nature of Internet traffic
  • quantify deployment of protocol features
  • Interesting for
  • Network engineers and protocol developers
  • Network modeling and simulation community
  • Network security and intrusion detection

4
Introduction Related work
  • Directional differences on backbone traffic
  • Evident on simple packet header analysis
  • Correlation of packets might reveal reasons
  • Related work
  • Mainly unidirectional flow data (NetFlow)
  • Either low or very high aggregation level
  • Marginal discussion on directional differences

5
Introduction Our contribution
  • Complete view on different levels
  • Contemporary data
  • Packet level analysis
  • Bi-directional TCP connections
  • Specific measurement location
  • Medium aggregation level
  • Suitable for highlighting directional differences

6
Introduction Measurement location
Internet
  • 2x 10 Gbit/s (OC-192)
  • 2x DAG6.2SE Cards
  • tightly synchronized
  • capturing headers

Sthlm
Stud-Net
Regional ISPs
Gbg
Chalmers Univ.
Göteborgs Univ.
7
Introduction General traffic characteristics
  • Data from 20 days in April 2006
  • 146 traces, 10.7 billion frames, 7.5 TB
  • 99.99 IPv4 data
  • 93 TCP packets
  • 97 TCP data
  • Data and packet counts equal on inbound and
    outbound links!

8
Highlights IP level
  • Distinct IP addresses seen (in Millions)

9
Highlights IP level
  • Distinct IP addresses seen (in Millions)
  • Surprisingly large numbers
  • Inbound destinations gtgt outbound sources
  • Outside hosts primarily due to UDP

10
Highlights TCP level
  • Connection attempt breakdown (Millions)


11
Highlights TCP level
  • Connection attempt breakdown (Millions)
  • Inbound connections mainly scans!


12
Highlights TCP level (2)
  • TCP termination behavior (Millions)

13
Highlights TCP level (2)
  • TCP termination behavior (Millions)
  • Only 67 close properly (2xFIN)
  • Inbound 20 of conn. closed by FIN and RST!

14
Highlights TCP level (3)
  • Statistical properties of established TCP
    connections
  • Lifetime, data volume, packet count
  • Inbound connections more likely to
  • show lifetimes between 1 and 5 seconds
  • be long lasting (gt10 minutes)
  • carry more data and more packets
  • show higher asymmetry (client-server pattern)

15
TCP level P2P traffic
  • Quantification according to port-numbers
  • Missing payload
  • ? underestimated by factor 2-3 ,
  • 13 of data in outbound connections
  • 25 of data in inbound connections

S. Sen et al, Accurate, Scalable
in-network identification of P2P traffic across
large networks, IMW 2002 T. Karagiannis et
al, Transport layer identification of P2P
Traffic, ACM SIGCOMM 2004
16
Highlights UDP level
  • 68 million UDP flows
  • 51 million carry less than 3 packets!
  • DNS 5 NTP 1.7
  • Incoming scanning gt 8
  • P2P overlay traffic gt 20
  • Signaling Traffic
  • Distributed Hash Table (DHT) like Kademlia
  • Update routing tables in decentralized way
  • Periodic ping queries and replies
  • P2P overlay networks span entire globe
  • High fluctuation in peering partners ? lots of
    IPs

17
Summary of results
  • Besides equal counts and volumes on both links,
    directional differences were found in
  • IP packet sizes
  • IP fragmentation
  • Number of TCP connections
  • TCP connection establishment termination
  • TCP option usage
  • TCP connection properties
  • UDP scanning traffic

18
Conclusion
  • High level analysis does not necessarily show
    differences ? detailed analysis does!
  • 2 main reasons for directional differences
  • Malicious traffic
  • the Internet is unfriendly
  • P2P
  • Göteborg is a P2P source
  • P2P is changing traffic characteristicse.g.
    packet sizes, TCP termination, TCP option usage

19
Thank you very much for you attention!
  • Questions?

20
BACKUP
  • BACKUP SLIDES

21
Common P2P port numbers
22
TCP level (4)
  • TCP options (in )

23
TCP level (4)
  • TCP options (in )

24
IP level (2)
  • Packet size distribution on the 2 links

25
IP level (2)
  • Packet size distribution on the 2 links

26
IP level (3)
  • IP fragmentation on the 2 links

27
Malicous traffic / P2P traffic
  • Connection properties

lifetime in sec
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