pfrazee / base-emoji Goto Github PK

Do we know what terminal support for emojis looks like across platforms? I know iterm2 renders them...

unicode is annoying to work with, you cant do split('') on the emoji string. would be nice to get a list of the emojis. im open to alternative solutions.

💡💳🛄🐗⛪💫⤵️🚏🚧🏬🍬🏦🛀➡️🍼🐗⬅️:donut:🔰👮🚸🔋💯©️🕛🎂😖🌼🔡🍰😞🌏

Hmm... github can't do donut.

Since GitHub now support 😢 😧 🙈 🙉 🙊 in the repo description I consider it a complete lack of 👀 of this project not to exploit that to the fullest 😉

Hello!

I wanted to implement your project in other languages, but I am not sure if I am legally allowed to do that. So open-sourcing your work would be a good idea.

would be nice to compress even more. 512 emojis could be good. Wish there were 1024 to make things easier for us.

I think we could optimize the emoji used,
there are some sets of emoji that are sort of similar, like multilpe different sorts of arrows,
one hump and two hump camels, several different buildings, etc, etc.
Also lots of clocks, it is probably easier to remember "clock" than 6:30

I've been thinking about actually experimentally testing this with a psychological experiment where people rember hashes encoded as hex, base64, and emoji, and detect how well they detect partial collisions by eye.

In a secure communication system, it is necessary at some point to verify keys.
Usually, this is represented as text key encoded as letters, hex, base32, base58 or maybe base64. Since a hash is a lot to deal with, often the hash is truncated to be easier for humans to process. (it's important not to truncate too much, or security will be lost https://evil32.com/ )

Humans have an approximately fixed capacity to remember things, and so when looking at a finger print, how many bits are they actually remembering? Since it seems the way humans work is they can remember (say) 7 things, but there is not a limit on the size of the set the 7 things are picked from. They could just as easily remember 7 animals as 7 digits.

Thus, to exand the security property of the user interface, if key fingerprints are displayed in a denser format (such as base emoji) then humans ought to be able to remember more bits, and thus have more secure fingerprints.

I want to test this in an experiment - i figure, a web page test subjects visit, and it associates keys with user names - then an attacker is simulated, where the subject must flag invalid keys that partially collide with their known keys.

The question is: does the detection success vary in proportion to encoding, and collision length?

@jbenet would love your ideas on this.

So far I have been unable to find any research on the usability of key fingerprints.

I propose:

4 alphabets:

• 😊 be256 - 1 emoji 1 byte
• 😀 be512 - 1 emoji 2 bytes
• 😃 be768 - 1 emoji 3 bytes
• 😄 be1024 - 1 emoji 4 bytes

notes:

• emoji are unicode, and we're picking alphabets, we already have tables at play.
• there's 1244 emoji, we could sacrifice 4 to be alphabet identifiers. I suggest those above (increasing in happiness 😄 ).
• Each should be contained in the other, so there's no ambiguity on what number they represent.
• You get a smiley face at the beginning of every (self-describing) emoji-text!! (it would make me so happy)
• if there is no leading encoding identifier (quirksmode), you assume the smallest alphabet possible (when you run into a character from a larger set you bump up to that. statistically, we're very unlikely to find sequences of bytes like: ([0-256]000)+ -- ie. [10, 0, 0, 0, 2, 0, 0, 0, ... ])

[ deleted a portion in which jbenet utterly fails to do simple math ]

Guys, be1024 is going to be huge sweet.

updates:

• added 🔥 to sha1, and "(+1 alphabet)"
• deleted math fail in which I claimed the equivalent of 2^10 = 2^32