Enigma   574

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Enigma Public
Welcome to Enigma Public, the world’s broadest collection of public data.
datasets  data  enigma  public  opendata 
4 weeks ago by areich
Enigma – Knocking On Forbidden Doors | Best Images Collections HD For Gadget windows Mac Android
Enigma – Knocking On Forbidden Doors Music video by Enigma performing Knocking On Forbidden Doors. (C) 2003 Baloo Music S.A., under exclusive license to Polydor/Island, a division of Universal Music GmbH http://vevo.ly/GXLVpx Enigma – Knocking On Forbidden Doors
IFTTT  WordPress  Forbidden  doors  Enigma  Knocking  on  Polydor  pop 
12 weeks ago by wotek
Decoding the Enigma with Recurrent Neural Networks • Github
Sam Greydanus:
<p>Now we’re ready for something a lot more complex: the Nazi Enigma. Its innards consisted of three rotating alphabet wheels, several switchboards, and ten cables. All told, the machine had 150,738,274,900,000 possible configurations!

<img src="https://greydanus.github.io/assets/enigma-rnn/enigma.gif" width="100%" />
<em>How the Enigma works. Note that the three wheels can rotate as the decoding process unfolds</em>

Background. Breaking the Enigma was an incredible feat - it even inspired the 2014 film The Imitation Game starring Benedict Cumberbatch as Alan Turing. Turing was one of the most important figures in the project. He also introduced the notion of Turing-completeness. In an ironic twist, we’ll be using a Turing-complete algorithm (the LSTM) to decode the Enigma.

We’ll train the model on only one permutation of switchboards, cables, and wheels. The keyword, then, is three letters which tell the model the initial positions of the wheels.

<img src="https://greydanus.github.io/assets/enigma-rnn/enigma-objective.png" width="100%" />
<em>Basic training objective where "EKW" is the keyword. The keyword defines the initial positions of the three alphabet wheels</em>

Making it happen. I synthesized training data on-the-fly using the crypto-enigma Python API and checked my work on a web-based Enigma emulator. I used each training example only once to avoid the possibility of overfitting.

The model needed to be very large to capture all the Enigma’s transformations. I had success with a single-celled LSTM model with 3000 hidden units. Training involved about a million steps of batched gradient descent: after a few days on a k40 GPU, I was getting 96-97% accuracy!</p>

Greydanus has done a lot of interesting stuff in this space. He's an undergraduate physics student at Dartmouth College in the US. His next project: trying to get RNNs to decode RSA-encoded text.
enigma  neuralnet 
july 2017 by charlesarthur
Decoding the Enigma with Recurrent Neural Networks
I am blown away by this -- given that Recurrent Neural Networks are Turing-complete, they can actually automate cryptanalysis given sufficient resources, at least to the degree of simulating the internal workings of the Enigma algorithm given plaintext, ciphertext and key:
The model needed to be very large to capture all the Enigma’s transformations. I had success with a single-celled LSTM model with 3000 hidden units. Training involved about a million steps of batched gradient descent: after a few days on a k40 GPU, I was getting 96-97% accuracy!
machine-learning  deep-learning  rnns  enigma  crypto  cryptanalysis  turing  history  gpus  gradient-descent 
july 2017 by jm
The Influence of ULTRA in the Second World War
"In 1993 Sir Harry Hinsley kindly agreed to speak about Bletchley Park, where he worked during the Second World War. Sir Harry Hinsley is a distinguished historian who during the Second World War worked at Bletchley Park, where much of the allied forces code-breaking effort took place." A transcript of the talk.
bletchley-park  world-war-II  encryption  enigma  history 
july 2017 by pw201

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