Simulation CSE598K/CSE545 - Advanced Network Security Prof. - - PowerPoint PPT Presentation

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Simulation CSE598K/CSE545 - Advanced Network Security Prof. - - PowerPoint PPT Presentation


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CSE598K/CSE545 - Advanced Network Security - McDaniel Page

Simulation

CSE598K/CSE545 - Advanced Network Security

  • Prof. McDaniel - Spring 2008

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SLIDE 2

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • Alan Turing - implementation of a state-

transition system (in proving properties

  • f algorithms/computing systems)
  • As systems security people, this is a

essential methodological tool.

  • Measurement vs. Emulation vs. Simulation
  • Measurement - measuring system behavior
  • Emulation - imitating system behavior
  • Simulation - modeling the entire

Simulation

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SLIDE 3

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • Measuring the behavior of the a system/environment/

phenomenon is too costly

  • Where you need to run many experiments (repetition)
  • Where the experiments take too long (time compression)
  • Where you need to control non-determinism (repeatability)
  • Where you need to instrument many/complex state

(measurement)

  • Goal: demonstrate the behavior of an environment as a

function of evolution and input parameters.

Why simulate?

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SLIDE 4

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • What is the model?
  • What does the input /output look like?
  • What is the simulator structure?
  • What do you need to measure?
  • Types of simulation
  • Trace-based simulation - using measurements of real

environment

  • Synthetic - all inputs and state are invented/created/derived

for experiment

Designing a simulator

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • A model is is conceptual device that abstracts the

features of reality that are not important (independent

  • f) the measured features?
  • What features of the environment do we want to measure?
  • What features should be deterministic/randomized?
  • What is the (simplified) state machine look like?
  • Decisions:
  • Real vs. virtual time?
  • Logical clocks help simplify complex interleaving of events
  • Monolithic vs. distributed simulation?
  • Distributed simulations introduce problems (synchronization) and

advantages (parallelization)

Model

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SLIDE 6

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

What makes a good model?

  • That which is ...
  • representative - reflects reality.
  • simulatable - can feasibly implement and run.
  • verifiable - can determine it is correct.

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • A workload is description or record of the simulated

environment

  • What is fixed?
  • What is variable?
  • Input parameters
  • What factors do you want to vary?
  • Continuous vs. discrete?
  • How do these factors increase the complexity of the simulator?
  • Caution: simulators with lots of input parameters can

get complex quickly, and the interactions between input parameters get subtler.

Simulator Input

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • What are the parameters that you want to measure or

need to track to show the simulated environment?

  • Performance
  • Cost
  • Change
  • Caution: to much/little makes post-processing difficult.
  • Note: Format output for post-evaluation (e.g., gnuplot)

Simulator Output

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • State transition diagram - a graphical representation of

the states and transitions of the system.

  • Common designs:
  • Clock - model time as discrete steps, visit each independent

element once per unit time

  • Event driven - model interesting events as events which fire

when some precondition is met

  • Hint: try to separate the invariant behavior from the

tunable/selectable (OO helps).

Simulation Design

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

A Generic Clock Design

  • Clock - model time as discrete steps, visit each

independent element once per unit time

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STOP

Init Loop Close

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SLIDE 11

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

A Generic Event Simulator

  • Event driven - model interesting events as events which

fire when some precondition is met

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STOP

Init Loop Close

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • A WebSoS overlay network under attack is under

attack, where every edge node is discovered by the DDoS adversary eventually. The host is promptly

  • DOSed. The adversary learns something that will aid

in future identification of the discovered hosts peers.

  • Goal: to discover how resilient the network is in

sustaining traffic in the presence of node discovery.

  • Model?
  • Inputs/Outputs?
  • What do you want to show?

An example: WebSoS

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Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • Validation is the process whereby the faithfulness of

the simulation is demonstrated.

  • Model verification shows that the conceptual model

reflects reality

  • Are the abstracted features truly independent?
  • What is lost virtualization of time or other features?
  • Can you quantify or explain the inaccuracies?
  • By proof: can you state the model as a mathematical

property you want to measure?

  • Investigate the construction STD

Validation

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SLIDE 14

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

  • Simulator validation show that you have implemented

the algorithms/model correctly?

  • Isolate each part of implementation (each algorithm)
  • Fix the randomness (where possible)
  • Hand-craft input, predict output
  • Run experiment
  • Validate output (inspection vs. statistical test)
  • Note: This is often one of the more complex and

difficult parts of simulation.

Simulator Validation

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SLIDE 15

Systems and Internet Infrastructure Security Laboratory (SIIS) Page

Homework

  • Complete the simulation experiment. See handout.

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