Noisy Challenge Writeup
What we have
For this challenge, we were told that a message was sent in a noisy environment. The message was in Morse, and repeated a few times.
We were given the script used to send the message (with the actual message and the number of repetitions redacted):
import numpy as np from random import gauss morse = REDACTED repeats = REDACTED pointed =  for c in morse: if c == ".": pointed.extend([1 for x in range(10)]) if c == "-": pointed.extend([1 for x in range(20)]) if c == " ": pointed.extend([0 for x in range(20)]) pointed.extend([0 for x in range(10)]) with open("points.txt", "w") as f: for _ in range(repeats): signal = pointed output =  for x, bit in enumerate(signal): output.append(bit + gauss(0,2)) signal = list(np.array(output) - .5) f.write('\n'.join([str(x) for x in signal])+"\n") f.close()
We were also given the file ‘points.txt’, which is a set of points (floats) that represent the value of the signal at a given point. The file is very long, so I won’t include it here.
What we need to do
We need to find out what was sent, ideally using the least amount of effort possible.
Since the gauss function was called with a mean of 0, we can assume that on average, the noise should be insignificant.
Our plan is then as follows:
- Average each set of 10 points into 1 value.
- Iterate over the set of averages, progressively increasing the expected length of the plaintext with each iteration
- Average the values at each position of the plaintext, for each expected length of the plaintext
- If there are any invalid values, discard this plaintext length and move to the next
- Print valid plaintext strings.
Note that when I say ‘Average’, I don’t mean literally averaging stuff. The positive signal is around 0.5, and the negative signal is around -0.5. What I mean is I am creating a confidence rating about whether the value is positive or negative. The sign of the value will indicate the sign of the signal, and the magnitude of the rating will determine how confident we are than the sign is correct.
We begin by testing to see if our plan will work. We make a copy of the source code we’re provided, and substitute in the morse code for ‘TESTMESSAGE’, with 15 repetitions (number chosen at random):
morse = "- . ... - -- . ... ... .- --. . " repeats = 15
We then write the values to a file (points.txt), and create our solution script:
#!/usr/bin/env python3 import itertools,collections # Read the file with the points file = open('points.txt', 'r') x =  # Add the floats to a list for line in file.readlines(): x.append(line[:-1]) summs =  # Sum up each group of 10 points for j in range(0,len(x),10): sum1 = 0 for q in range(10): sum1 += float(x[j + q]) summs.append(sum1) # Create a confidence rating about whether the signal at each position is positive or negative def solve(solLen): solution = [None] * solLen count = 0 def solVal(pos,val): if (val > 0): if solution[pos] == None: solution[pos] = 1 else: solution[pos] += 1 else: if solution[pos] == None: solution[pos] = -1 else: solution[pos] -= 1 for i in range(len(summs)): solVal(count,summs[i]) count += 1 if count == solLen: count = 0 return solution def consume(iterator, n): # Advance the iterator n-steps ahead. If n is none, consume entirely. collections.deque(itertools.islice(iterator, n), maxlen=0) # Convert the confidence rating to Morse code def toMorse(sol1): solStr = "" iterator = range(0, len(sol1)).__iter__() for i in iterator: if i >= len(sol1) - 1: solStr += '?' elif sol1[i] > 0: if sol1[i+1] > 0: solStr += '-' consume(iterator, 2) continue elif sol1[i] > 0: if sol1[i+1] < 0: solStr += '.' consume(iterator, 1) continue elif sol1[i] < 0: if sol1[i+1] < 0: solStr += ' ' consume(iterator, 2) continue else: solStr += '?' solStr += "." consume(iterator,1) return solStr def decryption(message): # Converts Morse code to character string. # Raises an exception if invalid characters are found #Code omitted for brevity. [Reference](https://www.geeksforgeeks.org/morse-code-translator-python/) print("Number of samples (/10): " + str(len(summs))) for ml in range(int(len(summs)/2)): try: sampleSol = solve(ml) print(decryption(toMorse(sampleSol))) except: continue
The script prints out “TESTMESSAGE”. All we have to do now is run it against the file with the actual points we’re given. The output is as follows:
Number of samples (/10): 2880 E A ANOISYNOISE ANOISYNOISUNOISYNOISE ANOISYNOISUNOISYNOISUNOISYNOISE ANOISYNOISUNOISYNOISUNOISYNOISUNOISYNOISE ANOISYNOISUNOISYNOISUNOISYNOISUNOISYNOISUNOISYNOISE ANOISYNOISUNOISYNOISUNOISYNOISUNOISYNOISUNOISYNOISUNOISYNOISE
The first valid string is the correct one, the rest are tainted due to the repetitions.