الصفحة 1
الصفحة 1
Hydra = هايدرا
Forgery involves the use of advanced algorithms to replicate and distribute deceptive products across various categories, casting shadows of doubt on the authenticity of goods. Although counterfeit detection can be useful in identifying and mitigating fraudulent activities, the widespread presence of counterfeit goods poses significant dangers, undermining consumer confidence and brand reputation. To underscore the severity of this issue, consider instances such as fake luxury items flooding the market, counterfeit electronics compromising safety, or bogus pharmaceuticals endangering health. Addressing this issue is critical in maintaining the integrity of brands, safeguarding consumer well-being, and preserving trust in the marketplace. The ability to distinguish between authentic and counterfeit products is paramount in ensuring accurate decision-making and preventing the harmful consequences of fraudulent goods. This technological context underscores the urgency of developing and deploying cutting-edge solutions to combat the evolving landscape of product forgery. Hydra emerges as a robust solution, utilizing a comprehensive approach that includes extracting posts and images from search engine tools, and is integrated with AI models to detect forgery. The Hydra platform not only provides users with a powerful tool for detecting counterfeit products but also offers tangible benefits such as enhanced brand security, increased awareness about the prevalence of forgeries, and the opportunity to actively participate in a real-time community.
Formal Techniques for Networked and Distributed Systems - FORTE 2008 ; 28th IFIP WG 6.1 International Conference Tokyo, Japan, June 10-13, 2008 Proceedings
This book constitutes the refereed proceedings of the 28th IFIP WG 6.1 International Conference on Formal Techniques for Networked and Distributed Systems, FORTE 2008, held in Tokyo, Japan, in June 2008 co-located with TestCom/FATES 2008.The 19 revised full papers and 1 revised short paper presented together with 1 invited talk were carefully reviewed and selected from 44 submissions. The papers cover new approaches, concepts and experience in the application of formal methods for the specification and verification of distributed systems and applications.
Deepfake detection
Recently, various techniques of manipulating the video content have become available to everyone – online, one can find free applications e.g., for face swapping in videos. Such universal accessibility carries a notable risk of flooding online content with false information, affecting not only the greats of this world, but also the whole societies, also the rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. It is therefore necessary to develop a verification tool that will help assess the authenticity of the videos posted on the internet. This project describes the approach of using artificial intelligence solutions to detect doctored videos.
