Accurately Measuring Denial of Service in Simulation and Testbed Experiments

Abstract

Researchers in the denial of service (DoS) field lack accurate, quantitative and versatile metrics to measure service denial in simulation and testbed experiments. Without such metrics, it is impossible to measure severity of various attacks, quantify success of proposed defenses and compare their performance. Existing DoS metrics equate service denial with slow communication, low throughput, high resource utilization and high loss rate. These metrics are not versatile because they fail to monitor all traffic parameters that signal service degradation. They are not quantitative because they fail to specify exact ranges of parameter values that correspond to good or poor service quality. Finally, they are not accurate since they were not proven to correspond to human perception of service denial. We propose several DoS impact metrics that measure the quality of service (QoS) experienced by end users during an attack. Our metrics are quantitative: they map QoS requirements for several applications into measurable traffic parameters with acceptable, scientifically-determined thresholds. They are versatile: they apply to a wide range of attack scenarios, which we demonstrate via testbed experiments and simulations. We also prove metrics accuracy through testing with human users.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 25, 2008
Accession Number
AD1000227

Entities

People

  • Alefiya Hussain
  • Jelena Mirkovic
  • Peter Reiher
  • Roshan K. Thomas
  • Sonia Fahmy

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Accuracy
  • Collateral Damage
  • Computer Science
  • Denial Of Service Attack
  • Floods
  • Information Science
  • Measurement
  • Network Topology
  • Order Statistics
  • Packet Loss
  • Perception
  • Simulations
  • Simulators
  • Statistics
  • Surveys
  • Topology
  • Transport Protocols

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Networking