Stavros D. Nikolopoulos

In today’s digital era of constant information sharing, ensuring the authenticity and integrity of digital documents—particularly portable document format (PDF) files—has become increasingly important. This paper introduces a watermarking scheme for PDF files by embedding quick response (QR) codes into the spatial domain of text color. The method takes a PDF and a QR code as input, resizing the QR code to match the length of the text on each page. The embedding process incorporates Arnold’s transformation and a permutation equal to the QR code’s size to secure both embedding and extraction. The QR code is applied by slightly altering the color of specific text characters that correspond to black pixels in the QR code image, achieving spatial-domain watermarking without degrading visual quality. Experimental evaluation demonstrates the method’s robustness against various attacks, with the watermarked PDFs achieving an average Peak Signal-to-Noise Ratio (PSNR) of 57.6 dB and Structural Similarity Index (SSIM) of 0.99. The extracted QR codes maintain PSNR values above 68.8 dB and SSIM equal to 1 after common processing attacks. The scheme also effectively detects malicious tampering, proving the potential of the proposed watermarking scheme in the protection of PDF files.

Non-Fungible Tokens (or, for short, NFT) establish the ownership and the authenticity of digital assets. Regardless the high security levels provided by blockchain, are not excluded the cases where the ownership of a digital object may be claimed without proper rights. Fraud and copyright infringement should be prevented through the insurance of the authenticity and the integrity of a digital object associated with an NFT. In this work we consider the case of NFT images under the aspect of being susceptible to duplication, theft, tampering, fraud, or in general any potential threat against their authenticity and integrity properties. To deal with such cases we propose an integrated system that provides an a priori embedding of authenticity and integrity related information by deploying robust authenticity information hiding in the frequency domain alongside fragile integrity information hiding in the spatial domain before the image is being publicly available as NFT. Moreover, an automated secure procedure for the development of smart contracts alongside the development of an NFT dual that serves as backup and is not publicly available through the marketplace is proposed in order to retain the initial digital image. We design a modular architecture that incorporates all the components proposed in this work and discuss its potentials on its deployment over different digital objects that can be considered as NFTs.

Malicious users may tamper forensic digital images for various reasons including among others the creation of false evidences. In this work we propose a tamper detection and localization technique for forensic digital images detecting whether a forensic image has been tampered and locating the area that has been modified. The methodology deploys the partition of the image into blocks and the calculation of the hash values of the red channel in particular areas of the image, the so-called integrity-blocks, embedding these values into the green channel of other blocks based on a permutation of the integrity-blocks. Moreover, once a tampering has been detected into a forensic image the derived system that implements the proposed method provides a visual evidence of the tampering by coloring the tampered area with red color identifying the extent and point of the tampering, making it easier to understand the issue and resolve it. We provide an experimental evaluation of the proposed technique by performing a set of attacks by both inserting and removing elements from forensic images proving the potentials of our model in detecting and precisely locating the tampered areas.

Watermarking is a method for the verification of the authenticity of a digital object. In this work we investigate the watermarking of audio signals utilizing watermarked images. We present a multiple watermarking scheme for the watermarking of digital audio signals. The proposed technique exploits an image as a watermark which has been already watermarked with a self inverting permutation. The watermarked image, is then embedded in the LSB values of the digital audio signal. By conducting a series of evaluation experiments, including an attack vector consisting of cropping, noise, and re-sampling attacks, we investigate the robustness of the proposed multiple watermarking technique and prove its potentials against various factors affecting each type of attack.

In this work, we developed an integrated simulation framework for pandemic prevention and mitigation of pandemics caused by airborne pathogens, incorporating three sub-models, namely the spatial model, the mobility model, and the propagation model, to create a realistic simulation environment for the evaluation of the effectiveness of different countermeasures on the epidemic dynamics. The spatial model converts images of real cities obtained from Google Maps into undirected weighted graphs that capture the spatial arrangement of the streets utilized next for the mobility of individuals. The mobility model implements a stochastic agent-based approach, developed to assign specific routes to individuals moving in the city, through the use of stochastic processes, utilizing the weights of the underlying graph to deploy shortest path algorithms. The propagation model implements both the epidemiological model and the physical substance of the transmission of an airborne pathogen (in our approach, we investigate the transmission parameters of SARS-CoV-2). The deployment of a set of countermeasures was investigated in reducing the spread of the pathogen, where, through a series of repetitive simulation experiments, we evaluated the effectiveness of each countermeasure in pandemic prevention.