2009
DOI: 10.1007/978-3-642-03317-9_22
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New Distinguishing Attack on MAC Using Secret-Prefix Method

Abstract: Abstract. This paper presents a new distinguisher which can be applied to secret-prefix MACs with the message length prepended to the message before hashing. The new distinguisher makes use of a special truncated differential path with high probability to distinguish an inner near-collision in the first round. Once the inner near-collision is detected, we can recognize an instantiated MAC from a MAC with a random function. The complexity for distinguishing the MAC with 43-step reduced SHA-1 is 2 124.5 queries.… Show more

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Cited by 10 publications
(7 citation statements)
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“…In this part, we adopt the techniques of detecting the inner near-collisions with some specific differences [19,20,21] to implement impossible differential cryptanalysis on Pelican, MT-MAC-AES and PC-MAC-AES, and all of them take the 4-round AES as the iteration function. Based on a 3-round impossible differential path of AES, we can recover the internal state of Pelican, which is an equivalent subkey, and the recovery leads to a selective forgery attack.…”
Section: Resultsmentioning
confidence: 99%
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“…In this part, we adopt the techniques of detecting the inner near-collisions with some specific differences [19,20,21] to implement impossible differential cryptanalysis on Pelican, MT-MAC-AES and PC-MAC-AES, and all of them take the 4-round AES as the iteration function. Based on a 3-round impossible differential path of AES, we can recover the internal state of Pelican, which is an equivalent subkey, and the recovery leads to a selective forgery attack.…”
Section: Resultsmentioning
confidence: 99%
“…While for MACs mentioned above, we have to explore new techniques to collect such message pairs since the 4-round AES is To get over this obstacle, we take advantage of the idea described in [19,20,21]. First, randomly choose two structures of messages, with the message differences of some specific forms.…”
Section: Message Pairs Collection Phasementioning
confidence: 99%
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