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I'm merely a hobbyist in this domain but isn't highly compressed data (like encrypted data) also high entropy? If this is finding patterns in the compressed da
by wayeq 3y ago
I'm merely a hobbyist in this domain but isn't highly compressed data (like encrypted data) also high entropy? If this is finding patterns in the compressed data to figure out which digit the uncompressed data represents, shouldn't those patterns be exploitable for better compression?
- fritzo 3y agoThe demonstration isn't classifying based on compressed data, rather it's classifying on the compressibility of data. The idea is that "7 7" should be more compressible than "7 3", and similarly raster images of "7 7" should be more compressible than raster images of "7 3".
- wayeq 3y agoAh ok, that makes sense. Thank you for the explanation.
- Zamicol 3y agoEncrypted data ideally is incompressible. Incompressibility is a hallmark of efficient cryptographic operations. See the Wikipedia article on Kolmogorov complexity, which has a short section about compression. https://en.wikipedia.org/wiki/Kolmogorov_complexity#Compression https://en.wikipedia.org/wiki/Kolmogorov_complexity#Compress... Edit: One of my favorite concepts in the domain of compression is the pigeonhole principle, that states that for all compression algorithms, some outputs will be larger than the inputs. Well designed encrypted payloads may be compressed, but the outputs should on average be larger than the inputs, rendering compression useless thus it is said to be "incompressible". https://en.wikipedia.org/wiki/Pigeonhole_principle#Uses_and_applications https://en.wikipedia.org/wiki/Pigeonhole_principle#Uses_and_...