Before revision: Given a set S of n d-dimensional points  , the k-nearest neighbors ( KNN) is the problem of quickly finding k points in S that are nearest to a query point q. The k-nearest neighbors problem has applications in machine learning for classification and regression and also in searching. The secure version of KNN where either q or S are encrypted, has applications such as providing services over sensitive (such as medical or localization) data .
After revision: Given a set S of n d-dimensional points , the k-nearest neighbors ( kNN) classifier assigns q with the majority class of its k nearest neighbors in S. In the secure version of KNN where either q or S are encrypted, has applications such as providing services over sensitive (such as medical or localization) data .