Collision attack

About: Collision attack is a research topic. Over the lifetime, 1093 publications have been published within this topic receiving 28389 citations.

Remote algorithmic complexity attacks against randomized hash tables

Abstract: Many network devices, such as routers, firewalls, and intrusion detection systems, usually maintain per-connection state in a hash table. However, hash tables are susceptible to algorithmic complexity attacks, in which the attacker degenerates the hash into a simple linked list. A common counter-measure is to randomize the hash table by adding a secret value, known only to the device, as a parameter to the hash function. Our goal is to demonstrate how the attacker can defeat this protection: we demonstrate how to discover this secret value, and to do so remotely, using network traffic. We show that if the secret value is small enough, such an attack is possible. Our attack does not rely on any weakness of a particular hash function and can work against any hash — although a poorly chosen hash function, that produces many collisions, can make the attack more efficient. We present a mathematical modeling of the attack, simulate the attack on different network topologies and finally describe a real-life attack against a weakened version of the Linux Netfilter.

Improving scalability in vehicular communication using one-way hash chain method

Abstract: Improving road safety and optimizing road traffic relies on both Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. The successful deployment of vehicular communication depends on the two contentious factors, security and privacy. Though several researches have been conducted on the issuance of pseudonyms to deal with these issues, the traditional PKI based schemes used for the generation of these pseudonyms produce an enormous signing and verification costs. In order to address this problem, we propose a novel scheme in which the RSUs in a VANET use a one-way hash chain scheme to generate a series of public/private key pairs and to distribute them along with an n bit hash code H@^ and a proof cipher C@^ to the vehicles in its range. Since the RSU will provide a synchronized clock to all vehicles, anytime a vehicle can verify another vehicle by combining the vehicle's public key and its n bit hash code, which should prove the same cryptographic hash function of the receiving vehicle. Through this proposed Hash-chain based Authentication Protocol (HAP), the certificate costs of messages are immensely reduced. Moreover, if an attacker tries to compromise a node's public key it will be infeasible for him/her to achieve the desired task, as the vehicle frequently changes its public/private keys in a random fashion and hence guarantees a secured vehicle communication. We analyzed the proposed protocol extensively to validate its better performance when compared to its counterparts.

One-way Hash Function Based on Neural Network

Abstract: A hash function is constructed based on a three-layer neural network. The three neuron-layers are used to realize data confusion, diffusion and compression respectively, and the multi-block hash mode is presented to support the plaintext with variable length. Theoretical analysis and experimental results show that this hash function is one-way, with high key sensitivity and plaintext sensitivity, and secure against birthday attacks or meet-in-the-middle attacks. Additionally, the neural network's property makes it practical to realize in a parallel way. These properties make it a suitable choice for data signature or authentication.

Collision-resistant hashing: Towards making UOWHFs practical

Abstract: Recent attacks on the cryptographic hash functions MD4 and MD5 make it clear that (strong) collision-resistance is a hard-to-achieve goal. We look towards a weaker notion, the universal one-way hash functions (UOWHFs) of Naor and Yung, and investigate their practical potential. The goal is to build UOWHFs not based on number theoretic assumptions, but from the primitives underlying current cryptographic hash functions like MD5 and SHA-1. Pursuing this goal leads us to new questions. The main one is how to extend a compression function to a full-fledged hash function in this new setting. We show that the classic Merkle-Damgard method used in the standard setting fails for these weaker kinds of hash functions, and we present some new methods that work. Our main construction is the XOR tree. We also consider the problem of input length-variability and present a general solution.

Stochastic Collision Attack

Abstract: On the one hand, collision attacks have been introduced in the context of side-channel analysis for attackers who exploit repeated code with the same data without having any knowledge of the leakage model. On the other hand, stochastic attacks have been introduced to recover leakage models of internally processed intermediate secret variables. Both techniques have shown advantages and intrinsic limitations. Most collision attacks, for instance, fail in exploiting all the leakages (e.g., only a subset of matching samples are analyzed), whereas stochastic attacks cannot involve linear regression with the full basis (while the latter basis is the most informative one). In this paper, we present an innovative attacking approach, which combines the flavors of stochastic and collision attacks. Importantly, our attack is derived from the optimal distinguisher, which maximizes the success rate when the model is known. Notably, we develop an original closed-form expression, which shows many benefits by using the full algebraic description of the leakage model. Using simulated data, we show in the unprotected case that, for low noise, the stochastic collision attack is superior to the state of the art, whereas asymptotically and thus, for higher noise, it becomes equivalent to the correlation-enhanced collision attack. Our so-called stochastic collision attack is extended to the scenario where the implementation is protected by masking. In this case, our new stochastic collision attack is more efficient in all scenarios and, remarkably, tends to the optimal distinguisher. We confirm the practicability of the stochastic collision attack thanks to experiments against a public data set (DPA contest v4). Furthermore, we derive the stochastic collision attack in case of zero-offset leakage that occurs in protected hardware implementations and use simulated data for comparison. Eventually, we underline the capability of the new distinguisher to improve its efficiency when the attack multiplicity increases.