The task of a fast correlation attack is to efficiently restore the initial content of a linear feedback shift register in a stream cipher using a detected correlation with the output sequence. We show that by modeling this problem as the problem of learning a binary linear multivariate polynomial, algorithms for polynomial reconstruction with queries can be modified through some general techniques used in fast correlation attacks. The result is a new and efficient way of performing fast correlation attacks.

Fast correlation attacks through reconstruction of linear polynomials

https://hal.archives-ouvertes.fr/hal-02117763/document

Blind detection of interleaver parameters

We consider the problem of estimating the parameters of a convolutional encoder from noisy data observations, i.e. when encoded bits are received with errors. Reverse engineering of a channel encoder has applications in cryptanalysis when attacking communication systems and also in DNA sequence analysis, when looking for possible error correcting codes in genomes. We present a new iterative, probabilistic algorithm based on the Expectation Maximization (EM) algorithm. We use the concept of log-likelihood ratio (LLR) algebra which will greatly simplify the derivation and interpretation of our final algorithm. We show results indicating the necessary data length and allowed channel error rate for reliable estimation.

Parameter Estimation of a Convolutional Encoder from Noisy Observations

Channel encoder, which includes a forward error correcting (FEC) code followed by an interleaver, plays a vital role in improving the error performance of digital storage and communication systems In most of the applications, the FEC code and interleaver parameters are known at the receiver to decode and de-interleave the information bits, respectively But the blind/semi-blind estimation of code and interleaver parameters at the receiver will provide additional advantages in applications, such as adaptive modulation and coding, cognitive radio, non-cooperative systems, etc The algorithms for the blind estimation of code parameters at the receiver had previously been proposed and investigated for known FEC codes In this paper, we propose algorithms for the joint recognition of the type of FEC codes and interleaver parameters without knowing any information about the channel encoder The proposed algorithm classify the incoming data symbols among block coded, convolutional coded, and uncoded symbols Further, we suggest analytical and histogram approaches for setting the threshold value to perform code classification and parameter estimation It is observed from the simulation results that the code classification and interleaver parameter estimation are performed successfully over erroneous channel conditions The proposed histogram approach is more robust against the analytical approach for noisy transmission environment and system latency is one of the important challenges for the histogram approach to achieve better performance

Classification of Error Correcting Codes and Estimation of Interleaver Parameters in a Noisy Transmission Environment

We focus on the problem of recovering the length and synchronization of a linear block code from an intercepted bitstream. We place ourselves in an operational context where the intercepted bitstream contains a realistic noise level. We present two algorithms, one due to Valembois and the other one brand new. They are both useful in different contexts, able to verify if a given length/synchronization is correct. Using them, we were able to practically recover the synchronization of several codes.

/pdf/recovering-a-code-s-length-and-synchronization-from-a-noisy-10r92uwqmb.pdf

Recovering a code's length and synchronization from a noisy intercepted bitstream

In this paper, we present a new algorithm for recovering a linear block code from noisy codewords. To achieve this, we introduce a version of Gallager algorithm with weighted parity-check equations. This new algorithm efficiently recovers LDPC codes and can also be used for other block codes.

Block code reconstruction using iterative decoding techniques

We present here a new technique to reconstruct punctured convolutional codes from a noisy intercepted bit-stream. Compared to existing techniques our algorithm has two major advantages: it can tolerate much higher noise levels in the bitstream and it is able to recover the best possible decoder (in terms of decoding complexity). This is achieved by identifying the exact puncturing pattern that was used and recovering the parent convolutional code.

/pdf/reconstruction-of-punctured-convolutional-codes-4iv3zulgss.pdf

Reconstruction of punctured convolutional codes

We present different techniques to reconstruct a linear scrambler from the knowledge of a large segment of the output stream according to various assumptions on the input stream. We also present some algebraic methods to reconstruct a synchronous scrambler when its output is known up to a linear transformation per block only.

Reconstruction of a Linear Scrambler

This article deals with the problem of quantifying how many noisy codewords have to be eavesdropped in order to reverse engineer a code The main result of this paper is a lower bound on this quantity and the proof that this number is logarithmic in the length for LDPC codes

/pdf/on-the-code-reverse-engineering-problem-19wrm6okp8.pdf

Mathieu Cluzeau

Papers

Block code reconstruction using iterative decoding techniques

Recovering a code's length and synchronization from a noisy intercepted bitstream

Reconstruction of punctured convolutional codes

Reconstruction of a Linear Scrambler

On the code reverse engineering problem