## Faugère-Lachartre implementation for linear algebra for Gröbner bases

Fayssal’s code which implements the Faugère-Lachartre approach to linear algebra for Gröbner bases is available on Github now. Fayssal did a Master’s project on linear algebra for Gröbner bases in the team of Jean-Charles Faugère.

## A Fully Homomorphic Cryptosystem with Approximate Perfect Secrecy

At CT-RSA 2013 a paper titled “A Fully Homomorphic Cryptosystem with Approximate Perfect Secrecy” by Michal Hojsík and Veronika Půlpánová was presented. Here is the abstract:

We propose a new fully homomorphic cryptosystem called Symmetric Polly Cracker (SymPC) and we prove its security in the information theoretical settings. Namely, we prove that SymPC approaches perfect secrecy in bounded CPA model as its security parameter grows (which we call approximate perfect secrecy). In our construction, we use a Gröbner basis to generate a polynomial factor ring of ciphertexts and use the underlying field as the plaintext space. The Gröbner basis equips the ciphertext factor ring with a multiplicative structure that is easily algorithmized, thus providing an environment for a fully homomorphic cryptosystem.

The proposal seems to have succeeded where we could not: a fully homomorphic encryption scheme that also is information theoretic secure. Indeed, the authors reference our work and point out that they are taking a different approach (from ours) which allows them to succeed in realising these two goals.

To understand the claim made, here’s a quick rehash of our Symmetric Polly Cracker (SPC) for d=1 and b=2.

The secret key is a Gröbner basis . To encrypt we pick  and publish where is the message we want to encrypt. Decryption is easy if we know because it is equivalent to computing normal forms modulo . Indeed, it can be shown that the problem of finding under a chosen plaintext attack is as hard as finding which we assume is a hard problem. This scheme is homomorphic: we can do additions and multiplications of ciphertexts which decrypt to the sums and products of plaintexts. However, the scheme is not fully homomorphic as the ciphertext size increases with each multiplication. Also, the problem of computing the Gröbner basis becomes easy once we published many encryptions, so the scheme only supports a limited number of encryptions. So far, so general.

Now, let’s take a look at the new approach. Despite the claim that “A Fully Homomorphic Cryptosystem with Approximate Perfect Secrecy” is a new approach, it is – as far as I can see – a tweak of this general construction (essentially going back to Koblitz and Fellows). The two tweaks are:

1. is augmented with the so-called “field polynomials” as they evaluate to zero on every element of (Note: the actual construction is slightly different, which I ignore here for clarity of presentation).
2. Instead of limiting the number of encryptions to some such that the Gröbner basis problem is assumed to be hard, the number of encryptions is limited to some value .

The first tweak means that after a certain number of multiplications ciphertexts do not grow in size any more. That is, the largest monomial (under some degree compatible ordering) is . This allows to call the scheme “compact” and hence allows to declare it a fully homomorphic scheme under the technical definition of compactness. Yet, this means that ciphertexts are exponentially big in (e.g., if , we are talking about ciphertexts with bits). I am not convinced these should be called “compact”.

The second tweak implies that a computationally unbound attacker’s chance of breaking the scheme approaches zero as approaches infinity. There simply aren’t enough equations to recover . Hence, at the cost of making the scheme exceptionally short-lived it is information theoretic secure (asymptotically).

## Linear Algebra for Gröbner Bases over GF(2): M4RI

Two days ago I wrote about LELA’s implementation of Gaussian elimination for Gröbner basis computations over $\mathbb{F}_2$. Yesterday, I implemented LELA’s algorithm (which is from Faugere & Lachartre paper) in M4RI. Continue reading “Linear Algebra for Gröbner Bases over GF(2): M4RI”

## Linear Algebra for Gröbner Bases over GF(2): LELA

The Efficient Linear Algebra for Gröbner Basis Computations workshop in Kaiserslautern two weeks ago was a welcome opportunity to finally test out LELA, a library specifically written for linear algebra for Gröbner basis computations including for GF(2). The library implements the “Faugère-Lachartre” algorithm (a similar trick, though less developed, appeared before in PolyBoRi) and uses M4RI for dense parts over GF(2).

So, I ran my benchmark matrices through LELA, discovered a bug in the process, then Bradford returned the favour and discovered a bug in M4RI … Finally, below are the timings. The column PLE is the PLE algorithm as implemented in M4RI, M4RI is the M4RI algorithm as implemented in M4RI, GB is a very naive variant of the algorithm LELA uses and LELA is, well, LELA.

 problem m n density PLE M4RI GB LELA HFE 25 12307 13508 0.076 1.0 0.5 0.8 0.56 HFE 30 19907 29323 0.067 4.7 2.7 4.7 3.42 HFE 35 29969 55800 0.059 19.3 9.2 19.5 13.92 Mutant 26075 26407 0.184 5.7 3.9 2.1 12.07 n=24, m=26 37587 38483 0.038 20.6 21.0 19.3 7.72 n=24, m=26 37576 32288 0.040 18.6 28.4 17.0 4.09 SR(2,2,2,4) c 5640 14297 0.003 0.4 0.2 0.1 0.40 SR(2,2,2,4) c 13665 17394 0.013 2.1 3.0 2.0 1.78 SR(2,2,2,4) c 11606 16282 0.035 1.9 4.4 1.5 0.81 SR(2,2,2,4) 13067 17511 0.008 1.9 2.0 1.3 1.45 SR(2,2,2,4) 12058 16662 0.015 1.5 1.9 1.6 1.01 SR(2,2,2,4) 115834 118589 0.003 528.2 578.5 522.9 48.39

What this table means is that one can expect more than an order of magnitude of speed-up when using LELA – which is dedicated to these computations – instead of M4RI – which does not have the specialised algorithm implemented yet. For very small matrices sometimes M4RI/PLE win, but then not by a large margin. The only row where LELA doesn’t do so good is Mutant, which – btw. – is not an F4 matrix but comes from the MXL2 algorithm.  It is possible that LELA’s sparse data structures are not that well equipped to deal with this rather dense matrix.

I am in the process of implementing the algorithm LELA uses in M4RI and will report updated timings here.

## Call for Papers: 3nd International Conference on Symbolic Computation and Cryptography

CIEM – Castro Urdiales, Spain, 11-13 July 2012, http://scc2012.unican.es/

## CALL FOR PAPERS

### IMPORTANT DATES

• Deadline for submission: April 28, 2012
• Notification of acceptance or rejection: May 18, 2012
• Deadline for final version: May 30, 2012
• Deadline for registration: June 12, 2012
• Deadline for special issue JSC: September 30, 2012

SCC 2012 is the third edition of a new series of conferences where  research and development in symbolic computation and cryptography may be presented and discussed. It is organized in response to the growing  interest in applying and developing methods, techniques, and software  tools of symbolic computation for cryptography. The use of Lattice  Reduction algorithms in cryptology and the application of Groebner  bases in the context of algebraic attacks are typical examples of  explored applications. The SCC 2012 conference is co-located with  third Workshop on Mathematical Cryptology (WMC 2012, http://wmc2012.unican.es/) , an event also organized by research group Algorithmic Mathematics  And Cryptography (AMAC), which will be held on 9-11 July 2012.

## Summer School on Tools :: Mykonos, Greece :: 28.5 – 1.6.

Slightly redacted announcement for the 2012 Summer School on Tools below.

Following the success of the ECRYPT Workshop on Tools for Cryptanalysis 2010,the ECRYPT II Symmetric Techniques Virtual Lab (SymLab) is pleased to announce the 2012 Summer School on Tools. Covering selected topics in both symmetric and asymmetric cryptography, this summer school will provide a thorough overview of some of the most important cryptographic tools that emerged in recent years. While the summer school is aimed primarily at postgraduate students, attendance is open to all. Continue reading “Summer School on Tools :: Mykonos, Greece :: 28.5 – 1.6.”

## SymbolicData

Sage has many optional packages, about 50 actually. However, it is not necessarily well known what some of these do. For example, recently William asked me to fix some issue in the optional database_symbolic_data (still needing review btw. hint hint) package which bought it back to my attention. Shortly after, Burcin mentioned to me that he spent considerable time copy’n’pasting some standard ideals from some package to Sage’s input format. Time which he probably wouldn’t have spent if he’d known about the SymbolicData.org database and it’s Sage interface. Here’s in it action: Continue reading “SymbolicData”