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首页> 外文期刊>Dependable and Secure Computing, IEEE Transactions on >Accurately Measuring Denial of Service in Simulation and Testbed Experiments
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Accurately Measuring Denial of Service in Simulation and Testbed Experiments

机译：在模拟和测试平台实验中准确测量拒绝服务

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摘要

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 experienced by 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.
机译：服务拒绝（DoS）领域的研究人员缺乏准确，定量和通用的指标来测量模拟和测试平台实验中的服务拒绝。没有这些指标，就无法衡量各种攻击的严重性，量化提议的防御措施的成功程度并比较其性能。现有的DoS指标将服务拒绝等同于通信速度慢，吞吐量低，资源利用率高和丢失率高。这些度量标准不是通用的，因为它们无法监视所有表示服务质量下降的流量参数。它们不是定量的，因为它们无法指定与良好或较差的服务质量相对应的参数值的确切范围。最后，它们不准确，因为没有被证明与人类对服务拒绝的看法相对应。我们提出了几种DoS影响指标，用于衡量用户在攻击过程中体验到的服务质量。我们的指标是定量的：它们将具有可接受的科学确定的阈值的多个应用程序的QoS需求映射到可测量的流量参数中。它们用途广泛：它们适用于广泛的攻击场景，我们通过测试平台实验和仿真进行了演示。我们还通过与人类用户进行测试来证明指标的准确性。

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