karthic

Additive Noise

The basic idea of the additive-noise-based perturbation technique is to add random noise to the actual data). The noise being added is typically continuous and with mean zero, which suits well continuous original data.

Algorithm:

1. Consider a data base D with n tuples t = {t1, t2....tn}.

Each tuples contains Set of attribute A = {A1, A2.....Am} A € ti.

2. Find the sensitive attribute SAR for all SAR € Ai € A (i=1,2...m).

3. Calculate Average for all SAR (i).

4. Do

Initialize the value i = (1, 2....n).

Check if (Average ≥ SAR (i.) to count the all values C1. Calculate M1 = (2*Average)/C1

Replace SAR (i). With M1.

Check if (Average ≤ SAR (i.) to count the all values C2. Calculate M2 = (2*Average)/C2

Replace SAR (i). With M2.

Increment the value of i.

5. While (i ≥ n) 6. End.

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