Uploading pictures to a cloud service may reveal, through automatic inference, scene information that a user might want to keep private. To protect images from automatic scene classification, we present a method that misleads the classifier while introducing only a minimal distortion and limiting the likelihood that the ground-truth class can be inferred from the processed image. The method, based on the Fast Gradient Sign Method (FGSM), generates adversarial images and leverages a multi-class scene classifier trained to select a target scene class.