print "\nAnalyzing message number %d: %s\n" % (msgNum+1, msg)
print "Message IC: %.4f" % msgIC
print "Message is likely %s\n" % ("polyalphabetic" if isPoly else "monoalphabetic")
# 3. For the ones which you suspect aren't monoalphabetic, they have been encrypted either using a Vignere cipher or Hills system. In order to differentiate, we shall apply the standard Vignere tests for keyword - the messages have specifically been chosen so that a Hills system message will be recognizable by how these tests perform.
if isPoly:
# (a) Find all repeated strings of lengths 3 or more and apply the Kasiski test.
kt = KasiskiTest()
kasiskiFailed = False
repeatedSubstrs = kt.getRepeatedSubstrs(msg, 3)
if repeatedSubstrs:
print "Repeated substrs of length >= 3:\n%s\n" % repeatedSubstrs
print "Potential keys determined by running Kasiski test on each substring:"
# print out potential key lengths for every substring
for keyLens in kt.getAllPotentialKeyLens(msg, repeatedSubstrs):
print keyLens
mostLikelyKeysKasiski = kt.getMostLikelyKeyLens(msg, repeatedSubstrs)
print "\nMost likely key lengths using Kasiski test:\n%s\n" % (mostLikelyKeysKasiski)
# initialize the letter frequency class
letFreq = LetterFrequency()
# loop through the top 4 most likely key lengths according to the kasiski test
for keyLen in mostLikelyKeysKasiski[:2]:
# Split the message into keyLen columns
msgColumns = polyCi.msgSplit(msg, keyLen)
# holds the potential keyword
keyword = ""
# perform frequency analysis on each column
