Improving the Security of Image Manipulation Detection through One-and-a-half-class Multiple Classification

journal Paper1
Authors: Mauro Barni, Ehsan Nowroozi, Benedetta Tondi
Year: 1019
Abstract: Protecting image manipulation detectors against perfect knowledge attacks requires the adoption of detector architectures which are intrinsically difficult to attack. In this paper, we do so, by exploiting a recently proposed multiple-classifier architecture combining the improved security of 1-Class (1C) classification and the good performance ensured by conventional 2-Class (2C) classification in the absence of attacks. The architecture, also known as 1.5-Class (1.5C) classifier, consists of one 2C classifier and two 1C classifiers run in parallel followed by a final 1C classifier…..

Higher-Order, Adversary-Aware, Double JPEG-Detection via Selected Training on Attacked Samples

Conference Paper1
Authors: Mauro Barni, Ehsan Nowroozi, Benedetta Tondi
Year: 2017
Abstract: In this paper we present an adversary-aware double JPEG detector which is capable of detecting the presence of two JPEG compression steps even in the presence of heterogeneous processing and counter-forensic (C-F) attacks. The detector is based on an SVM classifier fed with a large number of features and trained to recognise the traces left by double JPEG detection in the presence of attacks. Since it is not possible to train the SVM on all possible kinds of processing and C-F attacks, a selected set of images, manipulated with a limited number of attacks is added to the training set……