In this paper, we propose a new algorithm for solving the general approximate common divisors (GACD) problems, which is based on lattice reduction algorithms on certain special lattices and linear equation solving algorithms over integers. Through both theoretical arguments and experimental data, we show that our new algorithm works in polynomial time but under roughly the following condition: \begin{itemize} \item There is a positive integer t such that \frac{\gamma+\eta}{t} + \frac{t}{H} + \rho < \eta; \item We have more than t GACD samples. \end{itemize} or equivalently \begin{itemize} \item H(\eta-\rho)^2 - 4(\gamma+\eta) > 0; \item We have more than t = \lceil\frac{H(\eta-\rho) - \sqrt{H^2(\eta-\rho)^2 - 4H(\gamma+\eta)}{2}\rceil GACD samples. \end{itemize} Here \gamma, \eta and \rho are parameters describing a GACD problem, H = 1/\log_2 F and F is the Hermite Factor. In our experiments, H is shown to be roughly 40 when using the LLL reduction algorithm and it should be around 80 when using Deep or BKZ algorithms. % We use our algorithm to solve concrete problems that no other algorithm could solve before. We show how our algorithm can be applied to attack the fully homomorphic encryption schemes which are based on the general approximate common divisors problem and its limitations.

We present a new method for building pairs of HFE polynomials of high degree, such that the map constructed with such a pair is easy to invert. The inversion is accomplished using a low degree polynomial of Hamming weight three, which is derived from a special reduction via Hamming weight three polynomials produced by these two HFE polynomials. This allows us to build new candidates for multivariate trapdoor functions in which we use the pair of HFE polynomials to fabricate the core map. We performed the security analysis for the case where the base field is GF(2) and showed that these new trapdoor functions have high degrees of regularity, and therefore they are secure against the direct algebraic attack. We also give theoretical arguments to show that these new trapdoor functions over GF(2) are secure against the MinRank attack as well.

In this paper we present a new algorithm to attack lattice based cryptosystems by solving a problem over real numbers. In the case of the NTRU cryptosystem, if we assume the additional information on the modular operations, we can break the NTRU cryptosystems completely by getting the secret key. We believe that this fact was not known before.

We present a generalized learning with errors (LWE) problem, which is essentially a simple and direct extension of the original LWE problem to the case of matrices. Then we use this new version of LWE problem, which we call matrix LWE problem to build new cryptographic schemes, which include a new scalable key distribution scheme, a new key exchanges scheme and a new simple identity-based encryption scheme.

We use the learning with errors (LWE) problem to build a new simple and provably secure key exchange scheme. The basic idea of the construction can be viewed as certain extension of Diffie-Hellman problem with errors. The mathematical structure behind comes from the commutativity of computing a bilinear form in two different ways due to the associativity of the matrix multiplications: (x^t \times A)\times y = x^t \times (A\times y), where x,y are column vectors and A is a square matrix. We show that our new schemes are more efficient in terms of communication and computation complexity compared with key exchange schemes or key transport schemes via encryption schemes based on the LWE problem. Furthermore, we extend our scheme to the ring learning with errors (RLWE) problem, resulting in small key size and better efficiency.