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Chapter 7: Q18E (page 399)

Intrusion detection systems. The Journal of Research of the National Institute of Standards and Technology (November– December 2003) published a study of a computer intrusion detection system (IDS). The IDS is designed to provide an alarm whenever unauthorized access (e.g., an intrusion) to a computer system occurs. The probability of the system giving a false alarm (i.e., providing a warning when no intrusion occurs) is defined by the symbol α, while the probability of a missed detection (i.e., no warning given when an intrusion occurs) is defined by the symbol β. These symbols are used to represent Type I and Type II error rates, respectively, in a hypothesis-testing scenario

a. What is the null hypothesis, H0?

b. What is the alternative hypothesis,Ha?

c. According to actual data collected by the Massachusetts Institute of Technology Lincoln Laboratory, only 1 in 1,000 computer sessions with no intrusions resulted in a false alarm. For the same system, the laboratory found that only 500 of 1,000 intrusions were actually detected. Use this information to estimate the values of αand β.

Short Answer

Expert verified
  1. H0:No warning given when no intrusion occurs
  2. Ha:Warning given when an intrusion occurs
  3. The value of αandβare 0.001 and 0.5.

Step by step solution

01

Null hypothesis

a. The null hypothesis is given by:

H0:No warning given when no intrusion occurs

02

Alternative hypothesis

b. The alternative hypothesis is given by:

Ha:Warning given when an intrusion occurs

03

Computing the value of α and β

c. The value of αis computed as,

α=Number of computer sessions with no intrusionsTotal number of computer sessions=11000=0.001

The value of βis computed as,

β=Number of intrusions were actually detectedTotal number of intrusions=5001000=0.5

Therefore, the value of αandβare 0.001 and 0.5.

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Most popular questions from this chapter

: A random sample of n = 200 observations from a binomial population yield

p^=0.29

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c. Make the appropriate conclusion usingα=.10

Question: Testing the placebo effect. The placebo effect describes the phenomenon of improvement in the condition of a patient taking a placebo—a pill that looks and tastes real but contains no medically active chemicals. Physicians at a clinic in La Jolla, California, gave what they thought were drugs to 7,000 asthma, ulcer, and herpes patients. Although the doctors later learned that the drugs were really placebos, 70% of the patients reported an improved condition. Use this information to test (at α = 0.05) the placebo effect at the clinic. Assume that if the placebo is ineffective, the probability of a patient’s condition improving is 0.5.

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