Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userImplementing a Unification Algorithm for Protocol Analysis with XOR
125
0
0.0
(
0
)
Added by
Mathieu Turuani
Publication date
2006
fields
Informatics Engineering
and research's language is
English
Authors
Max Tuengerthal
Ask ChatGPT about the research
No Arabic abstract
In this paper, we propose a unification algorithm for the theory $E$ which combines unification algorithms for $E_{std}$ and $E_{ACUN}$ (ACUN properties, like XOR) but compared to the more general combination methods uses specific properties of the equational theories for further optimizations. Our optimizations drastically reduce the number of non-deterministic choices, in particular those for variable identification and linear orderings. This is important for reducing both the runtime of the unification algorithm and the number of unifiers in the complete set of unifiers. We emphasize that obtaining a ``small set of unifiers is essential for the efficiency of the constraint solving procedure within which the unification algorithm is used. The method is implemented in the CL-Atse tool for security protocol analysis.
rate research
Read More
Cryptographic protocols are often specified by narrations, i.e., finite sequences of message exchanges that show the intended execution of the protocol. Another use of narrations is to describe attacks. We propose in this paper to compile, when possible, attack describing narrations into a set of tests that honest participants can perform to exclude these executions. These tests can be implemented in monitors to protect existing implementations from rogue behaviour.
Oblivious transfer is a cryptographic primitive where Alice has two bits and Bob wishes to learn some function of them. Ideally, Alice should not learn Bobs desired function choice and Bob should not learn any more than what is logically implied by the function value. While decent quantum protocols for this task are known, many become completely insecure if an adversary were to control the quantum devices used in the implementation of the protocol. In this work we give a fully device-independent quantum protocol for XOR oblivious transfer which is provably more secure than any classical protocol.
Today, the Internet of Things (IoT) is one of the emerging technologies that enable the connection and transfer of information through communication networks. The main idea of the IoT is the widespread presence of objects such as mobile devices, sensors, and RFID. With the increase in traffic volume in urban areas, the existing intelligent urban traffic management system based on IoT can be vital. Therefore, this paper focused on security in urban traffic based on using RFID. In our scheme, RFID tags chose as the purpose of this article. We, in this paper, present a mutual authentication protocol that leads to privacy based on hybrid cryptography. Also, an authentication process with RFID tags is proposed that can be read at high speed. The protocol has attempted to reduce the complexity of computing. At the same time, the proposed method can withstand attacks such as spoofing of tag and reader, tag tracking, and replay attack.
Nonparametric learning is able to make reliable predictions by extracting information from similarities between a new set of input data and all samples. Here we point out a quantum paradigm of nonparametric learning which offers an exponential speedup over the sample size. By encoding data into quantum feature space, similarity between the data is defined as an inner product of quantum states. A quantum training state is introduced to superpose all data of samples, encoding relevant information for learning in its bipartite entanglement spectrum. We demonstrate that a trained state for prediction can be obtained by entanglement spectrum transformation, using quantum matrix toolbox. We further work out a feasible protocol to implement the quantum nonparametric learning with trapped ions, and demonstrate the power of quantum superposition for machine learning.
We dispel with street wisdom regarding the practical implementation of Strassens algorithm for matrix-matrix multiplication (DGEMM). Conventional wisdom: it is only practical for very large matrices. Our implementation is practical for small matrices. Conventional wisdom: the matrices being multiplied should be relatively square. Our implementation is practical for rank-k updates, where k is relatively small (a shape of importance for libraries like LAPACK). Conventional wisdom: it inherently requires substantial workspace. Our implementation requires no workspace beyond buffers already incorporated into conventional high-performance DGEMM implementations. Conventional wisdom: a Strassen DGEMM interface must pass in workspace. Our implementation requires no such workspace and can be plug-compatible with the standard DGEMM interface. Conventional wisdom: it is hard to demonstrate speedup on multi-core architectures. Our implementation demonstrates speedup over conventional DGEMM even on an Intel(R) Xeon Phi(TM) coprocessor utilizing 240 threads. We show how a distributed memory matrix-matrix multiplication also benefits from these advances.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
