Which cross-validation type best suits to binary classification problem
You will have best results if you care to build the folds so that each variable (and most importantly the target variable) is approximately identically distributed in each fold. This is called, when applied to the target variable, stratified k-fold. One approach is to cluster the inputs and make sure each fold contains the same number of instances from each cluster proportional to their size.