Postdoc at Royal Holloway on Lattice-based Cryptography

I am looking for a postdoc to join us to work on lattice-based cryptography. This postdoc is funded by the EU H2020 PROMETHEUS project for building privacy preserving systems from advanced lattice primitives. At Royal Holloway, the project is looked after by Kenny Paterson and me. Feel free to e-mail me with any queries you might have.

The ISG is a nice place to work; it’s a very friendly environment with strong research going on in several areas. We got people working across the field of information security including several people working on cryptography. A postdoc here is a 100% research position, i.e. you wouldn’t have teaching duties. That said, if you’d like to gain some teaching experience, we can arrange for that as well.

Also, if you have e.g. a two-body problem and would like to discuss flexibility about being in the office, feel free to get in touch.

Location Egham
Salary £36,654 per annum – including London Allowance
Closing Date Monday 17 September 2018
Interview Date To be confirmed
Reference 0818-334

The ISG is seeking to recruit a post-doctoral research assistant to work in the area of cryptography. The position is available now and will run until the end of 2021.

The PDRA will work alongside Dr. Martin Albrecht and other cryptographic researchers at Royal Holloway on topics in lattice-based cryptography. This post is part of the EU H2020 PROMETHEUS project (http://prometheuscrypt.gforge.inria.fr) for building privacy preserving systems from advanced lattice primitives. Our research focus within this project is on cryptanalysis and implementations, but applicants with a strong background in other areas such as protocol/primitive design are also encouraged to apply.

Applicants should have already completed, or be close to completing, a PhD in a relevant discipline. Applicants should have an outstanding research track record in cryptography. Applicants should be able to demonstrate scientific creativity, research independence, and the ability to communicate their ideas effectively in written and verbal form.

In return we offer a highly competitive rewards and benefits package including generous annual leave and training and development opportunities. This is a full time fixed term post is based in Egham, Surrey where the College is situated in a beautiful, leafy campus near to Windsor Great Park and within commuting distance from London.

Informal enquiries can be made to Martin Albrecht at martin.albrecht@royalholloway.ac.uk.

To view further details of this post and to apply please visit https://jobs.royalholloway.ac.uk/vacancy.aspx?ref=0818-334. For queries on the application process the Human Resources Department can be contacted by email at: recruitment@rhul.ac.uk.

Please quote the reference: 0818-334

Closing Date: Midnight, 17th September 2018

Interview Date: To be confirmed

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NTT Considered Harmful?

In a typical Ring-LWE-based public-key encryption scheme, Alice publishes

(a, b) = (a, a \cdot s + e) \in \mathbb{Z}_q[x]/(x^n+1)

(with n a power of two1) as the public key, where s, e are both “small” and secret. To encrypt, Bob computes

(c_{0}, c_{1}) = (v \cdot a + e', v \cdot b + e'' + \textnormal{Encode}(m))

where v, e', e'' are small, m is the message \in \{0,1\}^n and \textnormal{Encode}(\cdot) some encoding function, e.g. \sum_{i=0}^{n-1} \lfloor \frac{q}{2} \rfloor m_i x^i . To decrypt, Alice computes

c_{0} \cdot s - c_{1} = (v \cdot a + e')\cdot s - v \cdot (a\cdot s + e) + e'' + \textnormal{Encode}(m),

which is equal to e' \cdot s - v \cdot e + e'' + \textnormal{Encode}(m). Finally, Alice recovers m from the noisy encoding of m where e' \cdot s - v \cdot e + e'' is the noise. In the Module-LWE variant the elements essentially live in \left(\mathbb{Z}_q[x]/(x^n+1)\right)^k, e.g. a is not a polynomial but a vector of polynomials.

Thus, both encryption and decryption involve polynomial multiplication modulo x^n+1. Using schoolbook multiplication this costs \mathcal{O}(n^2) operations. However, when selecting parameters for Ring-LWE, we can choose q \equiv 1 \bmod 2n which permits to use an NTT to realise this multiplication (we require \equiv \bmod 2n to use the negacyclic NTT which has modular reductions modulo x^n+1 baked in). Then, using the NTT we can implement multiplication by

  1. evaluation (perform NTT),
  2. pointwise multiplication,
  3. interpolation (perform inverse NTT).

Steps (1) and (3) take \mathcal{O}(n \log n) operations by using specially chosen evaluation points (roots of one). Step (2) costs \mathcal{O}(n) operations.

This is trick is very popular. For example, many (but not all!) Ring-LWE based schemes submitted to the NIST PQC competition process use it, namely NewHope, LIMA (go LIMA!), LAC, KCL, HILA5, R.EMBLEM, Ding Key-Exchange, CRYSTALS-KYBER, CRYSTALS-DILITHIUM (sorry, if I forgot one). Note that since steps (1) and (3) are the expensive steps, it makes sense to remain in the NTT domain (i.e. after applying the NTT) and only to convert back at the very end. For example, it is faster for Alice to store s, e in NTT domain and, since the NTT maps uniform to uniform, to sample a in NTT domain directly, i.e. to just assume that a random vector a is already the output of an NTT on some other random vector.

This post is about two recent results I was involved in suggesting that this is not necessarily always the best choice (depending on your priorities.)

Warning: This is going to be one of those clickbait-y pieces where the article doesn’t live up to the promise in the headline. The NTT is fine. Some of my best friends use the NTT. In fact I’ve implemented and used the NTT myself.

Continue reading “NTT Considered Harmful?”

London-ish Lattice Coding & Crypto Meeting: 10 May 2017

Lattice-based approaches are emerging as a common theme in modern cryptography and coding theory. In communications, they are indispensable mathematical tools to construct powerful error-correction codes achieving the capacity of wireless channels. In cryptography, they are used to building lattice-based schemes with provable security, better asymptotic efficiency, resilience against quantum attacks and new functionalities such as fully homomorphic encryption.

This meeting — on 10 May 2017 — is aimed at connecting the two communities in the UK with a common interest in lattices, with a long-term goal of building a synergy of the two fields. It will consist of several talks on related topics, with a format that will hopefully encourage interaction.

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On dual lattice attacks against small-secret LWE and parameter choices in HElib and SEAL

My paper on solving small, sparse secret instances is now on ePrint. Here’s the abstract:

We present novel variants of the dual-lattice attack against LWE in the presence of an unusually short secret. These variants are informed by recent progress in BKW-style algorithms for solving LWE. Applying them to parameter sets suggested by the homomorphic encryption libraries HElib and SEAL yields revised security estimates. Our techniques scale the exponent of the dual-lattice attack by a factor of (2\,L)/(2\,L+1) when \log q = \Theta{\left(L \log n\right)}, when the secret has constant hamming weight h and where L is the maximum depth of supported circuits. They also allow to half the dimension of the lattice under consideration at a multiplicative cost of 2^{h} operations. Moreover, our techniques yield revised concrete security estimates. For example, both libraries promise 80 bits of security for LWE instances with n=1024 and \log_2 q \approx {47}, while the techniques described in this work lead to estimated costs of 68 bits (SEAL) and 62 bits (HElib).

If you want to see what its effect would be on your favourite small, sparse secret instance of LWE, the code for estimating the running time is included in our LWE estimator. The integration into the main function estimate_lwe is imperfect, though. To get you started, here’s the code used to produce the estimates for the rolling example in the paper.

  • Our instance’s secret has hamming weight h=64 and a ternary secret. We always use sieving as the SVP oracle in BKZ:

    sage: n, alpha, q = fhe_params(n=2048, L=2)
    sage: kwds = {"optimisation_target": "sieve", "h":64, "secret_bounds":(-1,1)}
    
  • We establish a base line:

    sage: print cost_str(sis(n, alpha, q, optimisation_target="sieve"))
    
  • We run the scaled normal form approach from Section 4 and enable amortising costs from Section 3 by setting use_lll=True:

    sage: print cost_str(sis_small_secret_mod_switch(n, alpha, q, use_lll=True, **kwds))
    
  • We run the approach from Section 5 for sparse secrets. Setting postprocess=True enables the search for solutions \mathbf{s}_1 with very low hamming weight (page 17):

    sage: print cost_str(drop_and_solve(sis, n, alpha, q, postprocess=True, **kwds))
    
  • We combine everything:

    sage: f = sis_small_secret_mod_switch
    sage: print cost_str(drop_and_solve(f, n, alpha, q, postprocess=True, **kwds))
    

London-ish Lattice Coding & Crypto Meeting: 21 September 2016

The next London-ish Lattice Coding & Crypto Meeting is coming up on September 21.

Programme

  • 11:00–12:30 | Jean-Claude Belfiore: Ideal Lattices: Connections between number fields and coding constructions
  • 13:30–15:00 | Dan Shepherd: Rings and Modules for Identity-Based Post-Quantum Public-Key Cryptography
  • 15:30–16:30 | Antonio Campello: Sampling Algorithms for Lattice Gaussian Codes
  • 16:30–17:00 | Cong Ling: Lattice Gaussian Sampling with Markov Chain Monte Carlo (MCMC)
  • 17:00–18:30 | Daniel Dadush: Solving SVP and CVP in 2^n Time via Discrete Gaussian Sampling

Venue

Arts Building Ground Floor Room 24
Royal Holloway, University of London
Egham Hill
Egham
Surrey TW20 0EX

See meeting website for details.

fpylll

fpylll is a Python library for performing lattice reduction on lattices over the Integers. It is based on the fplll, a C++ library which describes itself as follows:

fplll contains several algorithms on lattices that rely on floating-point computations. This includes implementations of the floating-point LLL reduction algorithm, offering different speed/guarantees ratios. It contains a ‘wrapper’ choosing the estimated best sequence of variants in order to provide a guaranteed output as fast as possible. In the case of the wrapper, the succession of variants is oblivious to the user. It also includes a rigorous floating-point implementation of the Kannan-Fincke-Pohst algorithm that finds a shortest non-zero lattice vector, and the BKZ reduction algorithm.

fplll is distributed under the GNU Lesser General Public License (either version 2.1 of the License, or, at your option, any later version) as published by the Free Software Foundation.

In short, fplll is your best bet at a publicly available fast lattice-reduction library and fpylll provides a convenient interface for it — for experimentation, development and extension — from Python.

For the rest of this post, I’ll give you a tour of the features currently implemented in fpylll and point out some areas where we could do with some help.

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