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IP Flow based intrusion detection


    Arangamanikkannan Manickam
IP Flow based Intrusion Detection


                Presented by
         Arangamanikkannan Manickam
Section Title
Overview
Issues with payload based NIDS
Sampling

    State information kept for each active flow

    Flow look-up for each incoming packet puts heavy
    demand on CPU and memory resources

    IETF PSAMP working group creating standards for
    sampling

    Makes intrusion detection harder

    Two categories:
      −   Packet sampling
      −   Flow Sampling
Sampling...

    Packet Sampling
       −   Systematic Sampling
             
                 Time-driven sampling
             
                 Event-driven sampling
       −   Random Sampling
             
                 Probability distribution function is used
                    −   n-inN sampling
                    −   Probabilistic sampling
Sampling...

    Flow Sampling
       −   Similar to random packet sampling
       −   Sample and hold method
             
                 A new incoming packet that does not
                 belong to existing flow leads to the creation
                 of new flow entry with probability p.
       −   Smart Sampling
             
                 Dynamically controls the size of sampled
                 data
             
                 Threshold sampling and priority
                 sampling
       −   Flow sampling probability depending on
Attack Classification

    Physical attacks

    Buffer overflow attacks

    Password attacks

    (Distributed) Denial of Service attacks

    Information gathering attacks

    Trojan horses

    Worms

    Viruses
Attack classification...

    Botnets
       −    Group of computers infected with
            malicious programs that cause them to
            operate against their owners' intentions
            and without their knowledge
       −    Remotely controlled by bot-masters
       −    Perfect for performing distributed attacks
Flow based Intrusion detection

    As it relies only the header information it
    addresses the following attacks
        −   Denial of service
        −   Scans
        −   Worms
        −   Botnets
IP flow based intrusion detection

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IP flow based intrusion detection

  • 1. IP Flow based intrusion detection Arangamanikkannan Manickam
  • 2. IP Flow based Intrusion Detection Presented by Arangamanikkannan Manickam
  • 5. Issues with payload based NIDS
  • 6.
  • 7. Sampling  State information kept for each active flow  Flow look-up for each incoming packet puts heavy demand on CPU and memory resources  IETF PSAMP working group creating standards for sampling  Makes intrusion detection harder  Two categories: − Packet sampling − Flow Sampling
  • 8. Sampling...  Packet Sampling − Systematic Sampling  Time-driven sampling  Event-driven sampling − Random Sampling  Probability distribution function is used − n-inN sampling − Probabilistic sampling
  • 9. Sampling...  Flow Sampling − Similar to random packet sampling − Sample and hold method  A new incoming packet that does not belong to existing flow leads to the creation of new flow entry with probability p. − Smart Sampling  Dynamically controls the size of sampled data  Threshold sampling and priority sampling − Flow sampling probability depending on
  • 10. Attack Classification  Physical attacks  Buffer overflow attacks  Password attacks  (Distributed) Denial of Service attacks  Information gathering attacks  Trojan horses  Worms  Viruses
  • 11. Attack classification...  Botnets − Group of computers infected with malicious programs that cause them to operate against their owners' intentions and without their knowledge − Remotely controlled by bot-masters − Perfect for performing distributed attacks
  • 12. Flow based Intrusion detection  As it relies only the header information it addresses the following attacks − Denial of service − Scans − Worms − Botnets