The SMS4 block cipher is part of the Chinese WAPI wireless standard. This paper describes the specification and offers a specification for a toy version called simplified SMS4 (S-SMS4). We explore algebraic attacks on SMS4 and S-SMS4 using Gröbner basis attacks on equation systems over GF(2) and GF(2^8), as well as attacks using a SAT solver derived from the GF(2) model. A comparison of SAT and Gröbner basis attacks is provided.

In 1998, Jeffrey Hoffstein, Jill Pipher, and Joseph H. Silverman introduced the famous NTRU cryptosystem, and called it "A ring-based public key cryptosystem". Actually, it turns out to be a lattice based cryptosystem that is resistant to Shor's algorithm. There are several modifications to the original NTRU and two of them are selected as round 2 candidates of NIST post quantum public key scheme standardization. In this paper, we present a simple attack on the original NTRU scheme. The idea comes from Ding et al.'s key mismatch attack. Essentially, an adversary can find information on the private key of a KEM by not encrypting a message as intended but in a manner which will cause a failure in decryption if the private key is in a certain form. In the present, NTRU has the encrypter generating a random polynomial with "small" coefficients, but we will have the coefficients be "large". After this, some further work will create an equivalent key.

No abstract uploaded!

No abstract uploaded!

Time- and state-domain methods are two common approaches to nonparametric prediction. Whereas the former uses data predominantly from recent history, the latter relies mainly on historical information. Combining these two pieces of valuable information is an interesting challenge in statistics. We surmount this problem by dynamically integrating information from both the time and state domains. The estimators from these two domains are optimally combined based on a data-driven weighting strategy, which provides a more efficient estimator of volatility. Asymptotic normality is separately established for the time domain, the state domain, and the integrated estimators. By comparing the efficiency of the estimators, we demonstrate that the proposed integrated estimator uniformly dominates the other two estimators. The proposed dynamic integration approach is also applicable to other estimation problems in time