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Credence 1.4.0

Credence is a robust and decentralized system for evaluating the reputation.


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For Credence 1.4.0Publisher's description


Credence is a Internet software developed by Kevin Walsh. After our trial and test, the software is proved to be official, secure and free. Here is the official description for Credence:

EditByBSEditor: Credence is a robust and decentralized system for evaluating the reputation of files in a peer-to-peer filesharing system. Our goal is to enable peers to confidently gauge file authenticity, the degree to which a file's contents matches its advertised description.

At the most basic level, Credence employs a simple, network-wide voting scheme where users can contribute positive and Negative evaluations of files. On top of this, a client uses statistical tests to weight the importance of votes from their peers. And finally, Credence allows clients to extend the horizon of information by selectively sharing information with their peers.
Authenticity and Pollution

We define pollution broadly as any file with content that does not match its description. An AUTHENTIC file, by contrast, has content that is accurately described by its metadata. We find in practice that pollution in current networks can be easily identified by users without any special knowledge or expertise. As pollution becomes more sophisticated, more advanced detection techniques will need to be developed to help users safely identify malicious content.

The Credence system relies on individual users as the first line of defense against pollution. After a user downloads and uses a file, she is given a chance to submit a single vote to the Credence system: a positive (thumbs-up) vote for authentic files, and a negative (thumbs-down) vote for a polluted file. Each vote is cryptographically signed and entered into the system.
Vote Gathering

Credence uses these votes collected in the network to determine the authenticity of content. Credence displays a rating for each file that appears in response to a user query.

First, the client software executes a search for votes, and downloads a number of votes randomly selected from the network. These votes are then aggregated into a single estimate of the authenticity of the file in question.
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