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The Internet has been weaponized to carry out cybercriminal activities at anunprecedented pace. The rising concerns for preserving the privacy of personaldata while availing modern tools and technologies is alarming. End-to-endencrypted solutions are in demand for almost all commercial platforms. On oneside, it seems imperative to provide such solutions and give people trust toreliably use these platforms. On the other side, this creates a hugeopportunity to carry out unchecked cybercrimes. This paper proposes a robustvideo hashing technique, scalable and efficient in chalking out matches from anenormous bulk of videos floating on these commercial platforms. The video hashis validated to be robust to common manipulations like scaling, corruptions bynoise, compression, and contrast changes that are most probable to happenduring transmission. It can also be transformed into the encrypted domain andwork on top of encrypted videos without deciphering. Thus, it can serve as apotential forensic tool that can trace the illegal sharing of videos withoutknowing the underlying content. Hence, it can help preserve privacy and combatcybercrimes such as revenge porn, hateful content, child abuse, or illegalmaterial propagated in a video.

Robust Homomorphic Video Hashing