Proteja seu espaço digital com o Detector Deepfake on-line da DeepBrain AI, projetado para identificar com rapidez e precisão o conteúdo gerado pela IA em minutos.
Reconheça facilmente vídeos deepfake avançados que são difíceis de detectar a olho nu.
Desenvolvida por algoritmos avançados de aprendizado profundo, a ferramenta de identificação deepfake do DeepBrain AI examina vários elementos do conteúdo de vídeo para diferenciar e detectar com eficácia diferentes tipos de manipulações de mídia sintética.
Carregue seu vídeo e nossa IA o analisará rapidamente, fornecendo uma avaliação precisa em cinco minutos para determinar se ele foi criado usando a tecnologia deepfake ou AI.
Detectamos com precisão várias formas deepfake, como trocas de rosto, manipulações de sincronização labial e vídeos gerados por IA, garantindo que você interaja com conteúdo autêntico e confiável.
Detecte vídeos e mídias manipulados com rapidez e precisão para se proteger contra uma ampla variedade de crimes de deepfake. A solução de detecção da DeepBrain AI ajuda a evitar fraudes, roubo de identidade, exploração pessoal e campanhas de desinformação.
Avançamos continuamente em nossa tecnologia para combater os deepfakes, proteger grupos vulneráveis e fornecer informações acionáveis contra a exploração digital. Estamos comprometidos em capacitar as organizações a proteger a integridade digital de forma eficaz.
Fornecemos nossas soluções e fazemos parcerias com as autoridades policiais, incluindo a Agência Nacional de Polícia da Coreia do Sul, para melhorar nosso software de detecção de deepfake para respostas mais rápidas a crimes relacionados.
O DeepBrain AI foi selecionado pelo Ministério da Ciência e TIC da Coreia do Sul para liderar o projeto “Deepfake Manipulation Video AI Data” em colaboração com o Laboratório de Pesquisa de IA da Universidade Nacional de Seul (DASIL).
Oferecemos uma demonstração gratuita de um mês para empresas, agências governamentais e instituições educacionais para combater crimes de vídeo gerados por IA e aprimorar suas capacidades de resposta.
Confira nossas perguntas frequentes para obter respostas rápidas sobre nossa solução de detecção de deepfake.
A deepfake is synthetic media created using artificial intelligence and machine learning techniques. It typically involves manipulating or generating visual and audio content to make it appear as if a person has said or done something that they haven't in reality. Deepfakes can range from face swaps in videos to entirely AI-generated images or voices that mimic real people with a high degree of realism.
DeepBrain AI's deepfake detection solution is designed to identify and filter out AI-generated fake content. It can spot various types of deepfakes, including face swaps, lip syncs, and AI/computer-generated videos. The system works by comparing suspicious content with original data to verify authenticity. This technology helps prevent potential harm from deepfakes and supports criminal investigations. By quickly flagging artificial content, DeepBrain AI's solution aims to protect individuals and organizations from deepfake-related threats.
Each deepfake detection system uses different techniques to spot manipulated content. DeepBrain AI’s deepfake detection process leverages a multi-step method to verify authenticity:
This multi-step approach allows DeepBrain AI to thoroughly analyze videos, images, and audio to determine if they are genuine or artificially created.
The accuracy of DeepBrain AI’s deepfake detection technology varies as the technology develops, but it generally detects deepfakes with over 90% accuracy. As the company continues to advance its technology, this accuracy keeps improving.
DeepBrain AI's current deepfake solution focuses on rapid detection rather than preemptive blocking. The system quickly analyzes videos, images, and audio, typically delivering results within 5–10 minutes. It categorizes content as "real" or "fake" and provides data on alteration rates and synthesis types.
Aimed at mitigating harm, the solution does not automatically remove or block content but notifies relevant parties like content moderators or individuals concerned about deepfake impersonation. The responsibility for action rests with these parties, not DeepBrain AI.
DeepBrain AI is actively working with other organizations and companies to make preemptive blocking a possibility. For now, its detection solutions help review suspicious content and assist in investigating fake deepfake videos to reduce further harm.
Major tech companies are actively responding to the deepfake issue through collaborative initiatives aimed at mitigating the risks associated with deceptive AI content. Recently, they signed the "Tech Accord to Combat Deceptive Use of AI in 2024 Elections" at the Munich Security Conference. This agreement commits firms like Microsoft, Google, and Meta to develop technologies that detect and counter misleading content, particularly in the context of elections. They are also developing advanced digital watermarking techniques for authenticating AI-generated content and partnering with governments and academic institutions to promote ethical AI practices. Additionally, companies continuously update their detection algorithms and raise public awareness about deepfake risks through educational campaigns, demonstrating a strong commitment to addressing this emerging challenge.
While major tech companies are making strides to combat deepfakes, their efforts may not be enough. The vast amount of content on social media makes it nearly impossible to catch every instance of manipulated media, and more sophisticated deepfakes can evade detection for longer periods.
For individuals and organizations seeking additional protection, specialized solutions like DeepBrain AI offer a valuable layer of security. By continuously analyzing internet media and tracking specific individuals, DeepBrain AI helps mitigate the risks associated with deepfakes. In summary, while industry initiatives are important, a multi-faceted approach that includes specialized tools and public awareness is essential for effectively tackling the deepfake challenge.