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<div class="moz-cite-prefix">On 2/23/22 17:49, Joshua Marpet wrote:<br>
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<blockquote type="cite"
cite="mid:CAC4EX57T9JrVmFk2rhNHDqcxNDkWaj8zZXXNSAYaUsY9Yo9FFA@mail.gmail.com">
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<div class="gmail_signature" data-smartmail="gmail_signature">I
was asked if anyone has performed/built commercially viable
implementations/products using homomorphic encryption and/or
structured encryption.</div>
<div class="gmail_signature" data-smartmail="gmail_signature"><br>
</div>
<div class="gmail_signature" data-smartmail="gmail_signature">I
found Tripleblind and I'm still trying to get a technical deep
dive with them.</div>
<div class="gmail_signature" data-smartmail="gmail_signature"><br>
</div>
<div class="gmail_signature" data-smartmail="gmail_signature">But!
Does anyone know a commercial product utilizing either
homomorphic or structured encryption?</div>
<div class="gmail_signature" data-smartmail="gmail_signature"><br>
</div>
<div class="gmail_signature" data-smartmail="gmail_signature">Thank
you in advance!</div>
<br>
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<br>
Structured encryption is a large and ambiguous topic, and I'm not
sure how many of the following are relevant to your intent.<br>
<br>
Block chain applications use linked hashes to create append-only
records. <br>
<br>
Merkle Trees are a fairly common way to give someone a small 'hash'
value that enables them to verify whether some document is or is not
part of a very large archive, and also a way to make recursive
queries down the tree to find some <br>
related values. This is typical in a lot of file sharing
applications. The user gets the 'root' of a Merkle tree and can then
make queries down the branches to find the document they're
interested in. <br>
<br>
File sharing applications also use structured hashing to identify
file chunks for retrieval purposes.<br>
<br>
Bloom filters are small-ish objects that a database can make
available to people allowing them to determine locally (subject to a
some degree of probabilstic chance) whether the database has a
particular object, without any further interaction with the database
after obtaining the filter. The good part of this is that the
queries the user makes are not transmitted and can't be
eavesdropped. Nobody can tell what the user searches for. The bad
part of this is that they provide no privacy to the database
server. If someone has a document hash, they can check the bloom
filter to see if the document is there - that includes both ordinary
users, and copyright trolls looking for people to sue. <br>
<br>
Bloom filters are also used in spelling checkers. The 'dictionary'
of many spell checkers is a Bloom Filter which you can query to
discover whether a word is, or is not, in the dictionary of known
words. It was the case early on that the Bloom Filter could be the
only reference - the spell checker didn't have a database of the
actual words anywhere. The results were sometimes humorous because
of that 'probabilistic' property, and you needed to make peace with
the idea that your spell checker now thinks 'argingg' or something
is a word because you added 'brownstone' to the dictionary. Modern
spell checkers actually have access to a list of words, and use
Bloom Filters as a 'shortcut.' They only look one up if the Filter
is inconclusive.<br>
<br>
Password testing tools use Rainbow Tables to check thousands of
passwords with each query whenever they can find a password database
where the passwords are encrypted but not salted. Rainbow Tables
have become less important since all serious software developers
have learned that salting passwords is absolutely necessary. That
said, a lot of not-very-serious software developers are nevertheless
entrusted with building customer databases. So security tools that
include a password breaker based on Rainbow Tables still find some
use.<br>
<br>
Are these examples of the kind of 'structured encryption' you were
asking about, or did you intend something more specific?<br>
<br>
Bear<br>
<br>
<br>
<br>
<br>
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