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Re: [tor-dev] Mnemonic 80-bit phrases (proposal)
Authors
Sai, Alex Fink
Overview
Currently, canonical Tor .onion URLs consist of a naked 80-bit
hash[1]. This is not something that users can even recognize for
validity, let alone produce directly. It is vulnerable to
partial-match fuzzing attacks[2], where a would-be MITM attacker
generates a very similar hash and uses various social engineering,
wiki poisoning, or other methods to trick the user into visiting the
spoof site.
This proposal gives an alternative method for displaying and entering
.onion and other URLs, such that they will be easily remembered and
generated by end users, and easily published by hidden service
websites, without any dependency on a full domain name type system
like e.g. namecoin[3]. This makes it easier to implement (requiring
only a change in the proxy).
This proposal could equally be used for IPv4, IPv6, etc, if normal DNS
is for some reason untrusted.
This is not a petname system[4], in that it does not allow service
providers or users[5] to associate a name of their choosing to an
address[6]. Rather, it is a mnemonic system that encodes the 80 bit
.onion address into a meaningful[7] and memorable sentence. A full
petname system (based on registration of some kind, and allowing for
shorter, service-chosen URLs) can be implemented in parallel[8].
This system has the three properties of being secure, distributed, and
human-meaningful â it just doesn't also have choice of name (except of
course by brute force creation of multiple keys to see if one has an
encoding the operator likes).
This is inspired by Jonathan Ackerman's "Four Little Words"
proposal[9] for doing the same thing with IPv4 addresses. We just need
to handle 80+ bits, not just 32 bits.
It is similar to Markus Jakobsson & Ruj Akavipat's FastWord
system[10], except that it does not permit user choice of passphrase,
does not know what URL a user will enter (vs verifying against a
single stored password), and again has to encode significantly more
data.
This is also similar to RFC1751[11], RFC2289[12], and multiple other
fingerprint encoding systems[13] (e.g. PGPfone[14] using the PGP
wordlist[15], and Arturo FilatsÃ's OnionURL[16]), but we aim to make
something that's as easy as possible for users to remember â and
significantly easier than just a list of words or pseudowords, which
we consider only useful as an active confirmation tool, not as
something that can be fully memorized and recalled, like a normal
domain name.
Requirements
1. encodes at least 80 bits of random data (preferably more, eg for a checksum)
2. valid, visualizable English sentence â not just a series of words[17]
3. words are common enough that non-native speakers and bad spellers
will have minimum difficulty remembering and producing (perhaps with
some spellcheck help)
4. not syntactically confusable (e.g. order should not matter)
5. short enough to be easily memorized and fully recalled at will, not
just recognized
6. no dependency on an external service
7. dictionary size small enough to be reasonable for end users to
download as part of the onion package
8. consistent across users (so that websites can e.g. reinforce their
random hash's phrase with a clever drawing)
9. not create offensive sentences that service providers will reject
10. resistant against semantic fuzzing (e.g. by having uniqueness
against WordNet synsets[18])
Possible implementations
1. Have a fixed number of template sentences, such as:
1. Adj subj adv vtrans adj obj
2. Subj and subj vtrans adj obj
3. â etc
For a 6 word sentence, with 8 (3b) templates, we need ~12b (4k word)
dictionaries for each word category.
If multiple words of the same category are used, they must either play
different grammatical roles (eg subj vs obj, or adj on a different
item), be chosen from different dictionaries, or there needs to be an
order-agnostic way to join them at the bit level. Preferably this
should be avoided, just to prevent users forgetting the order.
2. As (1), but treat sentence generation as decoding a prefix code,
and have a Huffman code for each word class. We suppose itâs okay if
the generated sentence has a few more words than it might, as long as
theyâre common lean words. E.g., for adjectives, âgoodâ might cost
only six bits while âunfortunateâ costs twelve.
Choice between different sentence syntaxes could be worked into the
prefix code as well, and potentially done separately for each
syntactic constituent.
Usage
To form mnemonic .onion URL, just join the words with dashes or
underscores, stripping minimal words like 'a', 'the', 'and' etc., and
append '.onion'. This can be readily distinguished from standard
hash-style .onion URLs by form.
Translation should take place at the client â though hidden service
servers should also be able to output the mnemonic form of hashes too,
to assist website operators in publishing them (e.g. by posting an
amusing drawing of the described situation on their website to
reinforce the mnemonic).
After the translation stage of name resolution, everything proceeds as
normal for an 80-bit hash onion URL.
The user should be notified of the mnemonic form of hash URL in some
way, and have an easy way in the client UI to translate mnemonics to
hashes and vice versa. For the purposes of browser URLs and the like
though, the mnemonic should be treated on par with the hash; if the
user enters a mnemonic URL they should not become redirected to the
hash version. (If anything, the opposite may be true, so that users
become used to seeing and verifying the mnemonic version of hash URLs,
and gain the security benefits against partial-match fuzzing.)
Ideally, inputs that don't validly resolve should have a response page
served by the proxy that uses a simple spell-check system to suggest
alternate domain names that are valid hash encodings. This could
hypothetically be done inline in URL input, but would require changes
on the browser (normally domain names aren't subject so spellcheck),
and this avoids that implementation problem.
International support
It is not possible for this scheme to support non-English languages without
a) (usually) Unicode in domains (which is not yet well supported by
browsers), and
b) fully customized dictionaries and phrase patterns per language
The scheme must not be used in an attempted 'translation' by simply
replacing English words with glosses in the target language. Several
of the necessary features would be completely mangled by this (e.g.
other languages have different synonym, homonym, etc groupings, not to
mention completely different grammar).
It is unlikely a priori that URLs constructed using a non-English
dictionary/pattern setup would in any sense 'translate' semantically
to English; more likely is that each language would have completely
unrelated encodings for a given hash.
We intend to only make an English version at first, to avoid these
issues during testing.
________________
[1] https://trac.torproject.org/projects/tor/wiki/doc/HiddenServiceNames
https://gitweb.torproject.org/torspec.git/blob/HEAD:/address-spec.txt
[2] http://www.thc.org/papers/ffp.html
[3] http://dot-bit.org/Namecoin
[4] https://en.wikipedia.org/wiki/Zooko's_triangle
[5] https://addons.mozilla.org/en-US/firefox/addon/petname-tool/
[6] However, service operators can generate a large number of hidden
service descriptors and check whether their hashes result in a
desirable phrasal encoding (much like certain hidden services
currently use brute force generated hashes to ensure their name is the
prefix of their raw hash). This won't get you whatever phrase you
want, but will at least improve the likelihood that it's something
amusing and acceptable.
[7] "Meaningful" here inasmuch as e.g. "Barnaby thoughtfully mangles
simplistic yellow camels" is an absurdist but meaningful sentence.
Absurdness is a feature, not a bug; it decreases the probability of
mistakes if the scenario described is not one that the user would try
to fit into a template of things they have previously encountered IRL.
See research into linguistic schema for further details.
[8] https://gitweb.torproject.org/torspec.git/blob/HEAD:/proposals/ideas/xxx-onion-nyms.txt
[9] http://blog.rabidgremlin.com/2010/11/28/4-little-words/
[10] http://fastword.me/
[11] https://tools.ietf.org/html/rfc1751
[12] http://tools.ietf.org/html/rfc2289
[13] https://github.com/singpolyma/mnemonicode
http://mysteryrobot.com
https://github.com/zacharyvoase/humanhash
[14] http://www.mathcs.duq.edu/~juola/papers.d/icslp96.pdf
[15] http://en.wikipedia.org/wiki/PGP_word_list
[16] https://github.com/hellais/Onion-url
https://github.com/hellais/Onion-url/blob/master/dev/mnemonic.py
[17] http://www.reddit.com/r/technology/comments/ecllk
[18] http://wordnet.princeton.edu/wordnet/man2.1/wnstats.7WN.html
[19] https://plus.google.com/u/0/103112149634414554669/posts/DLfvB76Zhav
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