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Perceptual video hashing in P2P networks
https://www.infona.pl/resource/bwmeta1.element.ieee-art-000005495380
Content identification in peer-to-peer (P2P) networks has until now been achieved by using metadata or cryptographic hashes. However, with increasing number of duplicates in different names and formats especially in (unmanaged) P2P networks, these tools have become insufficient for proper content finding and access right management.
Audio Fingerprinting In Peer-to-peer Networks. | Request …
https://www.researchgate.net/publication/220723029_Audio_Fingerprinting_In_Peer-to-peer_Networks
In this paper, we first discuss the essential requirements for a fingerprint (perceptual hash) based distributed video identification system in P2P networks in comparison with traditional central ...
Perceptual video hashing so that individuals can decide …
https://github.com/Chocobozzz/PeerTube/issues/214
There are perceptual video hashes which might allow the user to be prompted with "This video appears to have already been uploaded, if you share the existing video it will have better availability due to our P2P network." underneath would be embedded in the page the existing video and a share button.
(PDF) Perceptual Audio Hashing Functions
https://www.researchgate.net/publication/26531832_Perceptual_Audio_Hashing_Functions
Perceptual hash functions provide a tool for fast and reliable identification of content. We present new audio hash functions based on summarization …
Perceptual content identification in IPFS · Issue #15 ...
https://github.com/ipfs-inactive/faq/issues/15
A possible approach is to identify the content in P2P networks by using perceptual hashes (or fingerprints) extracted from the perceptual features of the content robust to typical processing. The uniform distribution of the extracted fingerprints enables the usage of existing DHT-based keyword search mechanisms for fingerprint queries.
A Fingerprinting System for Musical Content
http://www.cecs.uci.edu/%7Epapers/icme06/pdfs/0001989.pdf
tions can be foreseen for audio hashing such as: 1) content identi Þ cation; 2) broadcast monitoring; 3) connected audio; 4) Þ ltering technology for peer-to-peer (P2P) networks; 5) automatic music library organization. The proposed framework for robust perceptual hashing consists of two sub-systems: The Þ rst system generates of extracts the hash values from the
It's Not What It Looks Like: Manipulating Perceptual ...
https://gangw.cs.illinois.edu/PHashing.pdf
line social networks [16]. Perceptual hashing is also heavily used in real-world reverse image search engines such as Google [18], Yandex [83], Microsoft Bing [5], and TinEye [69]. Despite the wide adoption of perceptual hashing, the robust-ness of the algorithms is not well understood in the context of online abuse detection and analysis.
Perceptual Hashing - Bertolami.com
http://www.bertolami.com/index.php?engine=blog&content=posts&detail=perceptual-hashing
Perceptual Hashing. Wednesday, May 28th, 2014. Hash functions are an essential mathematical tool that are used to translate data of arbitrary size into a fixed sized output. There are many different kinds of these functions, each with their own characteristics and purpose. For example, cryptographic hash functions can be used to map sensitive information into hash …
Perceptual Image Hashing Based on Multitask Neural …
https://www.hindawi.com/journals/scn/2021/8297244/
Perceptual Image Hashing Based on Multitask Neural Network. Cheng Xiong,1 Enli Liu,1 Xinran Li,1 Heng Yao,1 Lei Zhang,1 and Chuan Qin1. 1School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. Academic Editor: Beijing Chen. Received 02 Nov 2021.
Perceptual hashing - Wikipedia
https://en.wikipedia.org/wiki/Perceptual_hashing
Perceptual hashing is the use of an algorithm that produces a snippet or fingerprint of various forms of multimedia. A perceptual hash is a type of locality-sensitive hash, which is analogous if features of the multimedia are similar. This is not to be confused with cryptographic hashing, which relies on the avalanche effect of a small change in input value creating a drastic change …
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