Related papers: ZK-IMG: Attested Images via Zero-Knowledge Proofs …
In the era of multimedia and Internet, people are eager to obtain information from offline to online. Quick Response (QR) codes and digital watermarks help us access information quickly. However, QR codes look ugly and invisible watermarks…
Zk-SNARKs help scale blockchains with Verifiable Off-chain Computations (VOC). zk-SNARK DSL toolkits are key when designing arithmetic circuits but fall short of automating the subsequent proof-generation step in an automated manner. We…
Cheapfake is a recently coined term that encompasses non-AI ("cheap") manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake media can be created using editing software for image/video…
With the increasing deployment of intelligent sensing technologies in highly sensitive environments such as restrooms and locker rooms, visual surveillance systems face a profound privacy-security paradox. Existing privacy-preserving…
Detecting deepfakes involving face-swaps presents a significant challenge, particularly in real-world scenarios where anyone can perform face-swapping with freely available tools and apps without any technical knowledge. Existing deepfake…
Fake News and especially deepfakes (generated, non-real image or video content) have become a serious topic over the last years. With the emergence of machine learning algorithms it is now easier than ever before to generate such fake…
Blockchain is a relatively new technology that can be seen as a decentralised database. Blockchain systems heavily rely on cryptographic hash functions to store their data, which makes it difficult to tamper with any data stored in the…
The rapid proliferation of realistic deepfakes has raised urgent concerns over their misuse, motivating the use of defensive watermarks in synthetic images for reliable detection and provenance tracking. However, this defense paradigm…
Deepfake technology, derived from deep learning, seamlessly inserts individuals into digital media, irrespective of their actual participation. Its foundation lies in machine learning and Artificial Intelligence (AI). Initially, deepfakes…
Industrial control systems (ICS) form the operational backbone of critical infrastructure networks (CIN) such as power grids, water supply systems, and gas pipelines. As cyber threats to these systems escalate, regulatory agencies are…
The rapid development of technologies and artificial intelligence makes deepfakes an increasingly sophisticated and challenging-to-identify technique. To ensure the accuracy of information and control misinformation and mass manipulation,…
In this study, we introduce a novel zero-knowledge identification scheme based on the hardness of the subgroup distance problem in the Hamming metric. The proposed protocol, named Subgroup Distance Zero Knowledge Proof (SDZKP), employs a…
This paper focuses on investigation of confidential documents leaks in the form of screen photographs. Proposed approach does not try to prevent leak in the first place but rather aims to determine source of the leak. Method works by…
Detecting AI-generated images remains a significant challenge because detectors trained on specific generators often fail to generalize to unseen models; however, while pixel-level artifacts vary across models, frequency-domain signatures…
Deepfake facial manipulation has garnered significant public attention due to its impacts on enhancing human experiences and posing privacy threats. Despite numerous passive algorithms that have been attempted to thwart malicious Deepfake…
Deepfakes pose a significant threat to digital media security, with current detection methods struggling to generalize across different manipulation techniques and datasets. While recent approaches combine CNN-based architectures with…
Payment channel network (PCN) is a layer-two scaling solution that enables fast off-chain transactions but does not involve on-chain transaction settlement. PCNs raise new privacy issues including balance secrecy, relationship anonymity and…
An increasing number of digital images are being shared and accessed through websites, media, and social applications. Many of these images have been modified and are not authentic. Recent advances in the use of deep convolutional neural…
Image embeddings are generally assumed to pose limited privacy risk. We challenge this assumption by formalizing semantic leakage as the ability to recover semantic structures from compressed image embeddings. Surprisingly, we show that…
Ensuring data privacy and protection has become paramount in the era of deep learning. Unlearnable examples are proposed to mislead the deep learning models and prevent data from unauthorized exploration by adding small perturbations to…