You can use randn()
t = 0:0.001:1;
x = cos(2*pi*100*t);
y = x+randn(size(t));
Of course that assumes you want N(0,1) additive noise. If you want zero-mean Gaussian white noise with a different variance, then use
y = x+sqrt(var_value)*randn(size(t));
where var_value is the variance you want.
