Ahmet Emir Dirik

Steganalytic Features for JPEG Compression-Based Perturbed Quantization

Perturbed quantization (PQ) data hiding is almost undetectable with the current steganalysis methods. We briefly describe PQ and propose singular value decomposition (SVD)-based features for the steganalysis of JPEG-based PQ data hiding in images. We show that JPEG-based PQ data hiding distorts linear dependencies of rows/columns of pixel values, and proposed features can be exploited within a simple classifier for the steganalysis of PQ. The proposed steganalyzer detects PQ embedding on relatively smooth stego images with 70% detection accuracy on average for different embedding rates

Forensic use of photo response non-uniformity of imaging sensors and a counter method

Analogous to use of bullet scratches in forensic science, the authenticity of a digital image can be verified through the noise characteristics of an imaging sensor. In particular, photo-response non-uniformity noise (PRNU) has been used in source camera identification (SCI). However, this technique can be used maliciously to track or inculpate innocent people. To impede such tracking, PRNU noise should be suppressed significantly. Based on this motivation, we propose a counter forensic method to deceive SCI. Experimental results show that it is possible to impede PRNU-based camera identification for various imaging sensors while preserving the image quality.

Detecting the Presence of ENF Signal in Digital Videos: A Superpixel-Based Approach

Electrical network frequency (ENF) instantaneously fluctuates around its nominal value (50/60 Hz) due to a continuous disparity between generated power and consumed power. Consequently, luminous intensity of a mains-powered light source varies depending on ENF fluctuations in the grid network. Variations in the luminance over time can be captured from video recordings and ENF can be estimated through content analysis of these recordings. In ENF-based video forensics, it is critical to check whether a given video file is appropriate for this type of analysis. That is, if ENF signal is not present in a given video, it would be useless to apply ENF-based forensic analysis. In this letter, an ENF signal presence detection method is introduced for videos. The proposed method is based on multiple ENF signal estimations from steady superpixels, i.e., pixels that are most likely uniform in color, brightness, and texture, and intra-class similarity of the estimated signals. Subsequently, consistency among these estimates is then used to determine the presence or absence of an ENF signal in a given video. The proposed technique can operate on video clips as short as 2 min and is independent of the camera sensor type, i.e., CCD or CMOS.

Forensic analysis of digital audio recordings based on acoustic mains hum

ENF (Electrical Network Frequency), fluctuates instantaneously from its nominal value (50/60 Hz) depending on an increase or decrease in power consumption as against power production in the grid network. An ENF-sourced noise component is added into audio recordings where mains power sourced electromagnetic field or acoustic mains hum exists. With the use of this component, recording date and time of an audio file can be verified. In this work, existence and estimation of the acoustic mains hum sourced ENF noise in audio files is studied by analysing the acoustic noise emitted by several devices that are frequently used at home or in workplace. Detection of the file recording time truly is examined by computation of the similarity between the ENF signals estimated from the audio recordings and the reference ENF obtained with the help of a circuit that is connected to power grid network. The behaviour of dynamic microphone and electret microphone towards acoustic mains hum is investigated and the extent of acquiring the information about recording device type and settings from audio files is analysed. Besides, as part of this work, ENF estimation from videos on social media is also investigated.

Source Attribution Based on Physical Defects in Light Path

Recent studies in multimedia forensics show that digital images contain intrinsic patterns, traces, and marks generated by imaging pipeline components (sensor) and processes (demosaicing and color adjustment). Some of these patterns and marks, such as photo response non-uniformity noise (PRNU), are unique to individual component characteristics of imaging system. Similar to PRNU noise, physical defects in imaging pipeline such as dust particles in DSLR camera chamber, scratches on flatbed scanners also generate unique patterns in image output. Due to unique and random nature of these patterns, they can be utilized in digital image forensics problems. In this chapter, we will give an overview of state-of-the-art camera identification techniques which utilize such defects and patterns.

You've got video: increasing clickthrough when sharing enterprise video with email

In this Note we summarize our research on increasing the information scent of video recordings that are shared via email in a corporate setting. We compare two types of email messages for sharing recordings: the first containing basic information (e.g. title, speaker, abstract) with a link to the video; the second with the same information plus a set of video thumbnails (hyperlinked to the segments they represent), which are automatically created by video summarization technology. We report on the results of two user studies. The first one compares the quality of the set of thumbnails selected by the technology to sets selected by 31 humans. The second study examines the clickthrough rates for both email formats (with and without hyperlinked thumbnails) as well as gathering subjective feedback via survey. Results indicate that the email messages with the thumbnails drove significantly higher clickthrough rates than the messages without, even though people clicked on the main video link more frequently than the thumbnails. Survey responses show that users found the email with the thumbnail set significantly more appealing and novel.

Steganalysis of Perturbed Quantization

Recently proposed perturbed quantization (PQ) data hiding is a novel steganographic scheme which is undetectable with the current steganalysis methods. In this paper PQ steganography scheme is described briefly and a novel singular value decomposition (SVD) based Steganalysis method is proposed to detect PQ embedding. The proposed SVD based steganalyzer detects PQ embedded relatively smooth stego images with 70% detection accuracy on average for different embedding rates