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Hide It in Plain Sight CS 490 Bob Orr
Cryptology 102 Hide It in Plain Sight CS 490 Bob Orr Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Transpositions Also called Permutations An encryption in which letters are rearranged rather than enciphered Goal is diffusion rather than confusion Attempts to break up obvious letter patterns Copyright © 2000 Trustees of Indiana University
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How the Transposition Works
The Message: THIS IS A MESSAGE TO SHOW HOW A COLUMNAR TRANSPOSITION WORKS Create a 5x10 matrix of the letters ~ fill with X’s, J’s & Q’s if necessary Transmit the message column by column Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Example T S O H A N I W L R M G U P E K C TSSOH OANIW HAASO LRSTO IMGHW UTPIR SEEOA MROOK ISTWC NASNS Copyright © 2000 Trustees of Indiana University
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Encipherment vs. Transposition
Enciphering takes the same amount of time per character and uses the same amount of storage space Transposition time is a function of message length; entire message must be stored initially before the message can be transposed; not well-suited for long messages Copyright © 2000 Trustees of Indiana University
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Digrams and Trigrams Top 10 Digrams EN RE ER NT TH ON IN TF AN OR
Top 10 Trigrams ENT ION AND ING IVE TIO FOR OUR THI ONE These are just as prevalent as individual characters and can be subjected to the same kind of relative frequency analysis ~ some like qp just don’t exist. Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Digram Analysis Less algorithmic than analysis of substitution ciphers More exhaustive and may depend ultimately on “what looks right” Initially, perform a letter frequency analysis when frequencies mirror that of English either a simple substitution, Caesar Cipher or transposition has been used Copyright © 2000 Trustees of Indiana University
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Possible Patterns TSSOH OANIW HAASO LRSTO IMGHW . . .
‘THI’ from THIS ‘SAM’ from [iS A Message] ‘SAG’ from [mesSAGe] Copyright © 2000 Trustees of Indiana University
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Digram Analysis cont’d
Trick is to determine the start of each column Process involves an exhaustive comparison of strings of ciphertext For example, group the first seven letters and then compare them to the 8th-14th letters, 9th-15th letters, and so forth until the digram patterns look right Called a Moving Window approach Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Moving Window N I W H A S O R T N I W H A S O R T N I W H A S O R T N I W H A S O R T N I W H A S O R T N I W H A S O R T Copyright © 2000 Trustees of Indiana University
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Statistical Analysis of Digram Occurrences
Calculate the means and standard deviations of all the digrams within each window A high mean indicates that the digrams are likely A low standard deviation suggests that all of the digrams are likely (mean is not distorted by a few popular digrams In this case, an offset of ten is best Copyright © 2000 Trustees of Indiana University
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Double Transpositions
Involves two column transpositions in succession with different numbers of columns for each transposition Technique diffuses characters more and scrambles digrams moreso than a single transposition will Disadvantage is that these are merely compound functions. Once a small bit is deciphered, the entire message unravels quickly Copyright © 2000 Trustees of Indiana University
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Double Transposition Example
TH I S I SAMES SAGET OSHOW HOWAC OLUMN ARTRA NSPOS I TI ON WORKS ORIGINAL TRANSPOSE TSSOH OANIW HAASO LRSTO IMGHW UTPIR SEEOA MROOK ISTWC NASNS THE RED LETTERS WILL SHOW THE DIFFUSION. Copyright © 2000 Trustees of Indiana University
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TNOMI MTSSI LGRRW XSWRH SOCXO HSWEO NXHAT UEKAX
Diffusion at Work TSSOHOA NIWHAAS OLRSTO I MGHWUTP I RSE E OA MROOKI S TWCNASN SXXXXXX TNOMI MTSSI LGRRW XSWRH SOCXO HSWEO NXHAT UEKAX OAOTO ISXAS IPASN X NOTE RED LETTERS ARE MORE SPREAD OUT - STILL MOSTLY IN TRIGRAM FORMAT 2nd TRANSPOSE (8 x 7) WITH X-FILL Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Stream Ciphers Convert one plaintext symbol directly into a ciphertext symbol. Transformation de- pends only on the symbol, the key and any control informa- tion needed by the encryption algorithm. Key (Optional) ISSOPMI Plaintext Wdhuw. . . Ciphertext Encryption Copyright © 2000 Trustees of Indiana University
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Stream Cipher Pros & Cons
Advantages Speed of Transformation Low error propagation Relative ease in deciphering of single errors ~ deletion of a single letter often results in recovery Disadvantages Low diffusion makes the ciphertext quite vulnerable to decryption efforts Susceptibility to malicious insertions or modifications - especially after key has been broken Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Block Ciphers Plaintext XN OI TP YR CN ES ba qc kd em mc Ciphertext po Encrypt a group of plain text symbols into a sin-gle block of ciphertext. Block sizes need not be related to the number of characters enciphered. Columnar transpositions are an example of this type of cipher. Copyright © 2000 Trustees of Indiana University
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Block Cipher Pros & Cons
Advantages Diffusion ~ one ciphertext block may depend on several plaintext characters. Immunity to Insertions because any such activity would alter block length and be detected. Disadvantages Slowness in execution at both ends of the system. Communication errors will render an entire block indecipherable (no easy method of recovery. Copyright © 2000 Trustees of Indiana University
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What Constitutes a “Good” Cipher?
Type of application Longevity of the data Environmental circumstances Copyright © 2000 Trustees of Indiana University
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Shannon Characteristics
Amount of secrecy needed should dictate the amount of labor needed to encrypt and decrypt a message. The set of keys and the enciphering algorithm should be free from complexity ~ don’t tie the algorithm to plaintext characteristics. Implementation of the process should be as simple as possible. Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
Shannon Continued Errors in ciphering should not propagate and cause corruption of further information in the message The size of the enciphered text should be no larger than the size of the plaintext Copyright © 2000 Trustees of Indiana University
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Confusion ~ Final Thoughts
Relates to the ease with which an interceptor can change one character in the plaintext and predict its impact on the ciphertext. Caesar ciphers have poor confusion Polyalphabetic substitutions provide good confusion especially if the key length exceeds message length Copyright © 2000 Trustees of Indiana University
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Diffusion ~ Final Thoughts
Relates to how well the enciphering algorithm spreads each plaintext character over the entire ciphertext. Substitution ciphers provide poor diffusion Transposition ciphers provide good diffusion Copyright © 2000 Trustees of Indiana University
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Secure Cryptographic Systems
Achieved if an interceptor cannot recover plaintext from ciphertext regardless of the time expended. One-time pads are perfect transfor- mations unless one assumes bribery, coercion or collusion between the sender and the receiver. Copyright © 2000 Trustees of Indiana University
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Secure Systems (cont’d)
A good encryption system is one that maps plaintext to zero, one, or many possible ciphertexts A cryptosystem is basically secure if the probability of applying the encryption function to the ciphertext to determine the plaintext is arbitrarily small. Copyright © 2000 Trustees of Indiana University
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generate N2 ciphertexts
The Perfect Scheme Keys P1 P2 . PN C1 C2 CN Normally, N keys and N plaintexts will generate N2 ciphertexts Copyright © 2000 Trustees of Indiana University
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An Imperfect Scheme Keys C1 More common: a single C2
ciphertext results from very few plaintext/key combinations. For example, knowing C1 was sent restricts the possible plaintexts to P2 or P3. Copyright © 2000 Trustees of Indiana University
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Information Theory ~ Redundancy
All languages are inherently redundant Consider the set of all 20-character messages: There are 2620 such messages Most will not make any sense but some will make perfect language sense. The difference between these two quantities defines a language’s redundancy Copyright © 2000 Trustees of Indiana University
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Redundancy Example AAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAB * *
* * AAAAAAAAAAAAAAAAAAAZ AAAAAAAAAAAAAAAAAABA ALLGOODTHINGSMUSTEND ZZZZZZZZZZZZZZZZZZZZ The set of possible messages of length 20 As you can see, most make no sense at all, but occasionally, one will make perfect sense. Copyright © 2000 Trustees of Indiana University
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Example Continued AAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAB * *
* * AAAAAAAAAAAAAAAAAAAZ AAAAAAAAAAAAAAAAAABA ALLGOODTHINGSMUSTEND ZZZZZZZZZZZZZZZZZZZZ By identifying and numerically coding all of the sensible messages, say on the interval [0,1023], we could transmit a message number rather than the actual message. Copyright © 2000 Trustees of Indiana University
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Copyright © 2000 Trustees of Indiana University
“Outta Here” Copyright © 2000 Trustees of Indiana University
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