It is the day after AsiaCrypt 2015 and there are two workshops being held in Auckland. The one which is most relevant for my research is that on Lattice Based Cryptography; which consists of four talks. One by Jung Hee Cheon on "Multilinear Maps and Their Cryptanalysis", one by Amit Sahai on "Obfuscation", one by Fre Vercauteren on "Weak Instances of RLWE" and one by Martin Albrecht on "Small Secret LWE".

Cheon first described a very naive version of multi-linear maps and then went on to show how this can be attacked by creating non-trivial encodings of zero, and then taking greatest common divisors. Then he went on to generalise this naive scheme to the CLT scheme (which is a bit like the DGHV FHE scheme). The naive attack does not apply to CLT as the dimension increased, meaning taking naive greatest common divisors would not work. Cheon then showed how to extend the naive attack to the CLT case by turning the gcd extraction into an eigenvalue extraction problem. This done by building quadratic forms which represent encodings of zero. The result is that for the CLT scheme one can break the equivalent of the DLP problem.

Cheon then went on to present the GGH scheme, which is a bit like the NTRU FHE scheme; except the instead of encrypting via c=[(m+r*p)/z] for an integer p, one encodes via c=[(m+r*g)/z] for a polynomial g which generates the ideal lattice <g>. Modifying the prior attack in this situation allows us to recover a basis of this ideal. But finding a short vector in this lattice can be hard. However, by utilizing encodings of zero one can actually solve the equivalent of the CDH problem.

Both attacks rely heavily on the presence of encodings of zero. So the attacks do not apply to situations in which one does not publish such encodings; i.e. applications such as indistinguishability Obfuscation (iO).

Amit Sahai then gave an introduction to iO; he motivated it via an analogy of an attacker who captures your brain and is able to read and tamper with every neuron, yet we still do not want the attacker to know what we are thinking about. This is the problem which obfuscation tries to solve in the computing realm. Martin pointed out that this would be a great way to produce malware!

Amit then put Multi-Party Computation within this analogy. He suggested we can think of MPC as protecting our brain against the tampering adversary, by dividing the brain up into portions. As long as one portion is kept out of the adversaries control we can use MPC to protect our thoughts. Obfuscation tries to do the same, without there needing to be an honest part of the brain.

Any program which is suitable for obfuscation must be unlearnable from query access to the program. Since otherwise the adversary could learn the program from the input/output behaviour. However, black-box obfuscation has been shown to be impossible; essentially because their are contrived programs which are unlearnable but for which one cannot produce an obfuscation, since any obfuscated program has an explicit attack against it.

This is why iO as a concept was presented; since it at least seems possible to achieve. The idea is that if you have two equivalent programs and we obfuscate one of them, then the adversary cannot tell which one we obfuscated. One way of thinking of this is as a psuedo-canonicalizer. The question is what useful can one do if we could create an obfuscator which satisfied the iO definition. Amit gave the application of building demo versions of software, without needing to re-engineer the software.

Fre Vercauteren then discussed a more in depth analysis of a paper from CRYPTO this year on Weak Instances of Ring-LWE. The CRYPTO paper gave instances where decision Ring-LWE was easy, but search appeared to be hard. However, Fre's talk showed that the search problem was in fact easy from the start, and thus the CRYPTO paper was less surprising than it at first seemed to be. As with all things on Ring-LWE the question arises as to how to choose the error distributions.

Fre spend the first part of his talk discussing the geometry of number fields, and in particular the Minkowski embedding. The Ring-LWE problem generates errors according to a discrete Gaussian distribution in the Minkowski embedding, Poly-LWE is to generate the errors according to a discrete Gaussian in the polynomial embedding.

Eisentrager et al discussed cases for which Poly-LWE was easy, these were then extended by Elias et al to special cases of decision Ring-LWE. They did this by mapping the special Ring-LWE instance to a special Poly-LWE instance.This is done by pulling back the problem from Ring-LWE to Poly-LWE via the matrix which defines the Minkowski embedding. The Poly-LWE attack requires that q is larger than f(1), and hence q will "kind of show up" in the coefficients of the defining polynomial f. So the fields being attacked, are very special indeed.

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