SIS with Hints Zoo
Table of Contents
An attempt to keep track of all those new SIS-like assumptions that hand out additional hints. Some of these venture into LWE land, but for now I want to keep it more or less SIS focused.
- Designers: Please consider whether you can re-use one of those many newfangled assumptions before introducing yet another one.
- Cryptanalysts: Analyse them!
In th jolly tradition of "Are Graded Encoding Schemes broken yet?" I tag problems as BROKEN if I am aware of cryptanalysis. I also tag them as:
- STANDARD
- if there is a reduction from a standard (non-hint) assumption that covers meaningful parameters, i.e. those useful in applications. For example, k-SIS is tagged like this but k-R-ISIS is not because known reductions only cover parameters that, so far, seem useless in applications.
- EQUIVALENT
- if there is a reduction from another hint assumption. Again, this may only cover some parameters. This is meant to indicate that cryptanalytic efforts might be better directed at the equivalent problem.
Please reach out if you find a mistake or have an update.
1. STANDARD k-SIS
We give the module variant defined in (Albrecht, Cini, Lai, Malavolta, & Thyagarajan, 2022). We recover the original definition by setting
For any integer
, an instance of the k-M-SIS problem is a matrix and a set of vectors s.t. with . A solution to the problem is a nonzero vector such that
An LWE variant, called k-LWE was introduced in (Ling, Phan, Stehlé, & Steinfeld, 2014).
1.1. Hardness
The original paper showed that k-SIS (over
The condition
No proof was provided for the module variant.
2. One-more-ISIS
(Agrawal, Kirshanova, Stehlé, & Yadav, 2022)
A challenger selects a matrix
and sends it to the adversary. The adversary can perform two types of queries: Syndrome queries The adversary can request a challenge vector which the challenger selects at random, i.e.
, adds to some set and returns to the adversary. Preimage queries. The adversary submits any vector
. The challenger will return a short vector such that . Denote for the number of preimage queries. In the end the adversary is asked to output
pairs satisfying:
2.1. Hardness
The hardness of the problem is analysed using direct cryptanalysis in the original paper. The authors give a combinatorial attack and a lattice attack.
Combinatorial Attack. The adversary requests
Lattice Attack. The adversary requests
3. K-R-ISIS
(Albrecht, Cini, Lai, Malavolta, & Thyagarajan, 2022)
Let
be a Laurent monomial, i.e. for some exponent vector . Let be a set of Laurent monomials with . Let be a target Laurent monomial. We call a family k-M-ISIS-admissible if
- all
have constant degree, i.e. ; - all
are distinct, i.e. is not a multiset; and . We call a family
k-M-ISIS-admissible if is k-MISIS-admissible, has constant degree, and .
Now, let
. Let be a set of -variate Laurent monomial. Let be a target Laurent monomial. Let be k-M-ISIS-admissible. Let , . The K-M-ISIS assumption states that given with short and it is hard to find a short and small s.t. When , i.e. when is just a vector, we call the problem k-R-ISIS.
3.1. Hardness
The hardness of the problem is analysed by the authors by providing some partial reductions, i.e. covering some special cases. These special cases are not interesting for applications. The authors show that
- k-R-ISIS (with
) is as hard as R-SIS when or when the system generated by is efficiently invertible. - k-M-ISIS is at least as hard as k-R-ISIS and that k-M-ISIS is a true generalisation of k-R-SIS.
is as hard as for any , formalising the intuition that the non-homogeneous variant is no easier than the homogeneous variant.- scaling
multiplicatively by any non-zero Laurent monomial does not change the hardness, e.g. we may choose to normalise instances to .
The authors also explore direct cryptanalysis:
- a direct SIS attack on
. - finding short
-linear combinations of - finding
-linear combinations of that produce short images.
4. BROKEN Knowledge K-R-ISIS
(Albrecht, Cini, Lai, Malavolta, & Thyagarajan, 2022)
The assumption essentially states that for any element
If an adversary outputs any
s.t. then there is an extractor that – with access to the adversary's randomness – outputs short s.t.
The knowledge assumption only makes sense for
4.1. Cryptanalysis
The assumption is invalidated – at least "morally" – in (Wee & Wu, 2023a). Roughly speaking, the attack uses that the preimages of
An implementation of the attack in SageMath is available here.
5. EQUIVALENT Twin K-R-ISIS
(Balbás, Catalano, Fiore, & Lai, 2022)
let
. Let be sets of -variate Laurent monomial. Let be k-M-ISIS-admissible. Let , , . The Twin K-M-ISIS assumption states that given with short, and it is hard to find a short s.t.
5.1. Hardness
In (Albrecht, Fenzi, Lapiha, & Nguyen, 2023), it is shown that Twin k-R-ISIS is no easier than k-R-ISIS via a re-randomisation argument.
6. STANDARD BASIS (Random)
We consider BASIS
Let
. We're given and a short s.t. where are uniformly random for and for uniformly random and . The BASIS
assumption states that given it is hard to find a short s.t. .
6.1. Hardness
It was shown in the original paper that BASIS
A way of looking at is by noting that for each column
7. EQUIVALENT BASIS (Structured)
We consider BASIS
Let
. We're given and a short s.t. where for known . The BASIS
assumption states that given it is hard to find a short s.t. .
7.1. Hardness
The authors also show that given an algorithm for solving BASIS
8. PRISIS
PRISIS (Fenzi & Nguyen, 2023) is a special case of BASIS. It is more structured than BASIS, so we might expect hardness results on PRISIS to translate to BASIS. It turns out the additional structure allows to prove a broader regime of parameters as hard as M-SIS.
Let
. We're given and a short s.t. The PRISIS assumption states that given
it is hard to find a short s.t. .
8.1. Hardness
If
9. STANDARD -PRISIS
Let
for . We're given and a short s.t. The
-PRISIS assumption states that given it is hard to find a short s.t. .
9.1. Hardness
10. ISISf
(Bootle, Lyubashevsky, Nguyen, & Sorniotti, 2023)
Let
and let be a function. Given and access to an oracle that when called samples a fresh and outputs s.t. the ISISf assumption states that it is hard to output a fresh tuple s.t.
10.1. Hardness
If
In (Bootle, Lyubashevsky, Nguyen, & Sorniotti, 2023) the authors set
Bibliography