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Data Sets with Events

Data Sets with no Events

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IEPM

[[rar

^datasets-with-events.rar]] 3.4 MB, [[zip

^datasets-with-events.zip]] 3.6 MB

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^datasets-with-no-events.zip]] 3.5 MB

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The technical report titled "A performance evaluation of anomaly detection algorithms for Internet Paths" is available here.

The range of input parameters used for the comparative analysis are summarized below. Note that each algorithm requires a different set of parameters.

Plateau Algorithm (PL)

History Buffer Length (H)

Trigger Buffer Length (T)

Threshold (th)

Sensitivity (s)

240

6 - 45

0.10 - 0.70

1.0 - 2.8

Kalman Filters Method (KF)

Sensitivity (K)

Time Window (h)

0.001 - 11.0

6 - 20

Holt Winter's Method (HW)

?

?

?

?

0.1

0.1 - 0.3

0.1 - 0.5

2.0

Adaptive Fault Detector (AFD)

Window Size (N)

?

?

No. of Training Data (Hn)

20

0.95

0.0015 - 0.1

100

Decision Theoretic Approach (DTA)

History Buffer Length (N)

?

?

Median filter length (thumbs down)

30 - 90

0.01 - 0.34 

0.99

100