Huge Multicollisions and Multipreimages of Hash Functions BLENDER-n

In this paper we present a multicollision and multipreimage attack on the hash function Blender-n [1] for all output sizes n = 224, 256, 384 and 512. The complexity and memory requirements for finding 2^{2n} multipreimages (multicollisions) of Blender-n is roughly 10 times more than finding a collision for n/2-bit random hash function. All previous attacks were based on the trick by Joux [2] using many messages. Our attacks are based on one message with several fixpoints. The state register has eight words. By properly choosing message words we force half of the register to go to the original state. Then we will find a collision in the rest with complexity 2^{n/4}. The collision creates a fix point in the sequence of states of the state register. We use 10 such fix points. Previously known attacks [4, 5] on Blender-n have the complexity at least 2^{n/2}. Our 2^{2n}-multicollision and multipreimage attacks have a complexity 10*2^{n/4}

Generic Attacks on Hash Functions

The subject of this thesis is a security property of hash functions, called chosen-target forced-prefix preimage (CTFP) resistance and the generic attack on this property, called the herding attack. The study of CTFP resistance started when Kelsey-Kohno introduced a new data structure, called a diamond structure, in order to show the strength of a CTFP resistance property of a hash function. In this thesis, we concentrate on the complexity of the diamond structure and its application in the herding attack. We review the analysis done by Kelsey and Kohno and point out a subtle flaw in their analysis. We propose a correction of their analysis and based on our revised analysis, calculate the message complexity and the computational complexity of the generic attacks that are based on the diamond structure. As an application of the diamond structure on generic attacks, we propose a multiple herding attack on a special generalization of iterated hash functions, proposed by Nandi-Stinson