I have read an interesting paper (pdf) describing how a privacy preserving technique might be breached, but I am having trouble understanding the following paragraph describing one of several layers of noise added to an observation.
Let C be a condition, e.g. "age = 34". The static noise associated with C is a random number drawn from a normal distribution N(0,1). The value is generated by a pseudo-random generator, whose seed is a salted hash of the string literal C:
static_seedC = XOR(hash(C), salt)
This ensures that the static noise associated with C is always the same independently from the query where C appears. The noise is "sticky" thereby preventing an attacker from sending the query many times and averaging the results to obtain a precise estimate of the private value ("averaging attack").
So if I understand correctly, the seed always generates the same number, let's say 0.4, so that C always becomes 34.4 instead of 34. If however C would sometimes be 33.9, 34.1, 34.2 and so forth, given enough trials the attacker would be able to draw a histogram which would be centered around 34 and infer that the age was 34?
If this is correct, can anyone please explain the equation above generating the noise (in this case the number 0.4)? I am not so familiar with the terms.