I-Corps: Deep Forgery Detection Technology

I-Corps：深度伪造检测技术

• 批准号: 2231092
• 负责人: Khalid Malik
• 金额: $ 5万
• 依托单位: Oakland University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2231092&HistoricalAwards=false
• 关键词: Corps; Deep; Forgery; Detection; Technology

The broader impact/commercial potential of this I-Corps project is the potential development of innovations to authenticate multimedia objects to be used as evidence in legal proceedings. Digital media admitted as legal evidence must meet court-defined values for authenticity, integrity, and veracity. Moreover, deep fakes or multimedia content that has been partially or completely computer-generated with the intent to deceive has progressed to a level where detection in some cases is beyond the ability of humans to achieve unassisted. In the legal public sector, this technology may be leveraged by a judge or court or used to gather evidence by the police, prosecutor, FBI, or other government entity. On the private side, its use is not only in courtrooms but in depositions, or during eDiscovery, a process already used for vetting electronic documents like email. This I-Corps project is based on the development of new technology to possibly detect audio-visual forgeries, including various types of deep fakes used in the manipulation and/or falsification of digital multimedia. Existing Forensic Examiners typically do not satisfy the requirements of criminal justice and social media platforms; they are limited in scope and are unable to answer complex questions regarding the nature of the forgery. This is particularly true when the media is recorded using low-powered devices and/or has been subjected to an anti-forensic attack. Unlike the state-of-the-art tools which rely on deep learning algorithms for pattern matching to detect single forgeries (e.g., video or voice deep fakes), this innovation uses a multimodal and neuro-symbolic artificial intelligence (AI) approach, and could detect multiple complex audiovisual forgeries, including deep fakes by performing the deep inspection at the file- and frame- levels.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个I-Corps项目的更广泛的影响/商业潜力是创新的潜在发展，以确认多媒体对象，以作为法律程序中的证据。被视为法律证据的数字媒体必须满足法院定义的价值观，以实现真实性，诚信和真实性。此外，已部分或完全计算机生成的深层假货或多媒体内容以欺骗的目的发展到某些情况下，在某些情况下检测超出了人类无助的能力。在法律公共部门中，该技术可以由法官或法院利用，也可以由警察，检察官，联邦调查局或其他政府实体收集证据。从私人方面来说，它的使用不仅在法庭上，而且在沉积中，或者在Ediscovery期间，该过程已经用于审查电子邮件之类的电子文档。这个I-Corps项目基于开发新技术，以检测视听伪造，包括用于操纵和/或伪造数字多媒体的各种深层假货。现有的法医考官通常不满足刑事司法和社交媒体平台的要求；它们的范围有限，无法回答有关伪造性质的复杂问题。当使用低功率设备录制媒体和/或经过抗法攻击时，尤其如此。与依靠深度学习算法进行模式匹配的最新工具不同，以检测单个伪造（例如，视频或语音深色伪造），这种创新使用多模式和神经符号的人工智能（AI）方法，并且可以检测多个复杂的听觉伪造，包括深度伪造的依据，并在包括files的范围内进行录音，并进行了验证，并可以进行档案，并绘制files的范围，并绘制了files的范围 - 使命，并被认为是通过基金会的知识分子优点和更广泛影响的审查标准通过评估值得支持的。