Digital Media Forensic Detection

We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional…

• AHMET MURAT TEKALP

We present techniques for steganalysis of images that have been potentially subjected to steganographic algorithms, both within the passive warden and active warden frameworks. Our hypothesis is that steganographic schemes leave statistical evidence that can be exploited for detection with the aid of image quality fea…

Several fragile watermarking schemes presented in the literature are either vulnerable to vector quantization (VQ) counterfeiting attacks or sacrifice localization accuracy to improve security. Using a hierarchical structure, we propose a method that thwarts the VQ attack while sustaining the superior localization pro…

• AHMET MURAT TEKALP

In this work, we focus our interest on blind source camera identification problem by extending our results in the direction of M. Kharrazi et al. (2004). The interpolation in the color surface of an image due to the use of a color filter array (CFA) forms the basis of the paper. We propose to identify the source camer…

Spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Vulnerability of recognition systems to spoofing attacks (presentation attacks) is still an open security issue in biometrics domain and among all biometric traits, face is exposed to the most serious threat, since i…

• NESLİ ERDOĞMUŞ

We present a novel framework for lossless (invertible) authentication watermarking, which enables zero-distortion reconstruction of the un-watermarked images upon verification. As opposed to earlier lossless authentication methods that required reconstruction of the original image prior to validation, the new framewor…

• AHMET MURAT TEKALP

Hardware, low power consumption, high accuracy and performance are crucial factors for deep learning applications. High level graphics processing units (GPU) are commonly used in high performance deep learning applications. However, it is a lot in terms of cost and power consumption to build a high-performance platfor…

Closed-circuit television cameras used today for surveillance sometimes enable privacy intrusion. The authors' privacy console manages operator access to different versions of video-derived data according to access-control lists. Additionally, their PrivacyCam is a smart camera that produces a video stream with privac…

We present a novel technique for steganalysis of images that have been subjected to embedding by steganographic algorithms. The seventh and eighth bit planes in an image are used for the computation of several binary similarity measures. The basic idea is that the correlation between the bit planes as well as the bina…

Deep Learning (DL) is the most efficient technique to handle a wide range of challenging problems such as data analytics, diagnosing diseases, detecting anomalies, etc. The development of DL has raised some privacy, justice, and national security issues. Deepfake is a DL-based application that has been very popular in…

In this paper, we introduce tamper detection techniques based on artifacts created by color filter array (CFA) processing in most digital cameras. The techniques are based on computing a single feature and a simple threshold based classifier. The efficacy of the approach was tested over thousands of authentic, tampere…

Abstract In recent years, the proliferation of deep learning (DL) techniques has given rise to a significant challenge in the form of deepfake videos, posing a grave threat to the authenticity of media content. With the rapid advancement of DL technology, the creation of convincingly realistic deepfake videos has beco…

• NIMA JAFARI NAVIMIPOUR