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7h
comment Does the One Time Pad rely on confusion or diffusion?
As I mulled over your answer, I came up with the following argument to say that the OTP only adds confusion: we can always consider that the OTP enciphers one message of length $n$, where $n$ is the sum of the lengths of all messages thus sent. This can be seen as choosing a random function $F$, and putting $c=F(m)$. Or in other words, the cipher consists of an "SBox" with the input size equal to $n$. Clearly this adds only confusion. Maybe the most important remark about Shannon's confusion & diffusion is that they are not exact concepts... (something he explicitly states in the paper).
May
23
asked Does the One Time Pad rely on confusion or diffusion?
Mar
27
awarded  Scholar
Mar
27
accepted Does perfect secrecy imply uniform ciphertext distribution?
Mar
25
comment Does perfect secrecy imply uniform ciphertext distribution?
No, I'm not trying to keep the same length. But could you give more details about your answer? You seem to be modifying an existing algorithm, but I do not see how this leads to non-uniformity in ciphertext distribution.
Mar
25
comment Does perfect secrecy imply uniform ciphertext distribution?
Unless I'm misunderstanding something, this does not work: if the key is chosen uniformly, both ciphertexts will have probability $0.5$. For example, the probability of $c=0$ is $0.8*0.5 + 0.2*0.5 = 0.5$. Or did you have in mind some other probability distribution for the key?
Mar
25
asked Does perfect secrecy imply uniform ciphertext distribution?
Aug
6
awarded  Supporter
Jul
11
asked Is OpenPGP vulnerable to the “crypto doom principle”?
Feb
22
comment Computational indistinguishability and example of non polynomial algorithm
(cont.) You mentioned exhaustive search, which is indeed non polynomial. But what does it mean to do exhaustive search when trying to distinguish two probability ensembles? To give a concrete example, what would it mean to do an exhaustive search in order to try to distinguish the output of a PRNG from the uniform distribution? Does this clarify what I am trying to ask?
Feb
22
comment Computational indistinguishability and example of non polynomial algorithm
I'll try to clarify my question. I am familiar with run time analysis of algorithms, and big-O notation, my question is not about that; it's about algorithms (or statistical tests if you will) that are capable of distinguishing two different (but computationally indistinguishable) probability ensembles. From all I've read, being indistinguishable means that there is no non-uniform probabilistic polynomial time algorithm could tell one ensemble from the other. However, I could not find an example of an algorithm that could distinguish the two ensembles, and that's what I asked for.
Feb
22
comment Computational indistinguishability and example of non polynomial algorithm
I understand the examples you give, but how would you apply them to a (sample from a) probability distribution? What would exhaustive search be like in this case? I mean, there is no "key" for which to check for correctness!
Feb
21
asked Computational indistinguishability and example of non polynomial algorithm
Nov
9
comment Randomized algorithms and the one time pad
@bob, thank you for your answer, it has been insightful. However, one doubt remains: what's the problem of "the key (one-time pad) is to be changed for each plaintext"? Isn't this the way one time pads are supposed to work? I think you I are referring to the fact that "my" one time pad does not include (explicitly) a key generation algorithm. Say I added one; borrowing from another answer, the key generation is done throwing dice. Would it then be semantically secure?
Nov
8
awarded  Student
Nov
8
comment Randomized algorithms and the one time pad
@bob probabilistic encryption refers to an algorithm receiving the same PT and key, and output varying output, right?
Nov
7
asked Randomized algorithms and the one time pad