The Internet has been weaponized to carry out cybercriminal activities at an unprecedented pace. The rising concerns for preserving the privacy of personal data while availing modern tools and technologies is alarming. End-to-end encrypted solutions are in demand for almost all commercial platforms. On one side, it seems imperative to provide such solutions and give people trust to reliably use these platforms. On the other side, this creates a huge opportunity to carry out unchecked cybercrimes. This paper proposes a robust video hashing technique, scalable and efficient in chalking out matches from an enormous bulk of videos floating on these commercial platforms. The video hash is validated to be robust to common manipulations like scaling, corruptions by noise, compression, and contrast changes that are most probable to happen during transmission. It can also be transformed into the encrypted domain and work on top of encrypted videos without deciphering. Thus, it can serve as a potential forensic tool that can trace the illegal sharing of videos without knowing the underlying content. Hence, it can help preserve privacy and combat cybercrimes such as revenge porn, hateful content, child abuse, or illegal material propagated in a video.

中文翻译：

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稳健的同态视频哈希

互联网已被武器化，以前所未有的速度开展网络犯罪活动。在利用现代工具和技术的同时保护个人数据隐私的担忧日益增加，令人担忧。几乎所有商业平台都需要端到端加密解决方案。一方面，提供此类解决方案并让人们信任可靠地使用这些平台似乎势在必行。另一方面，这为实施不受检查的网络犯罪创造了巨大的机会。本文提出了一种强大的视频散列技术，可扩展且有效地从这些商业平台上漂浮的大量视频中提取匹配项。视频哈希经验证对常见操作具有鲁棒性，例如缩放、噪声损坏、压缩、以及在传输过程中最有可能发生的对比度变化。它还可以转换为加密域，并在不解密的情况下在加密视频之上工作。因此，它可以作为一种潜在的取证工具，可以在不知道底层内容的情况下追踪视频的非法共享。因此，它可以帮助保护隐私并打击网络犯罪，例如复仇色情、仇恨内容、虐待儿童或视频中传播的非法材料。