Most modern block cipher today comprises of single nonlinear element which is called as substitution box. It comes with various of size depending on the cipher input and the secret key. Various methods have been proposed in order to construct it. In this paper, a new construction method has been proposed that is based on linear hybrid cellular automata (LHCA) iteration. There are specific number of combinations of rule 150 and rule 90 of elementary cellular automata (ECA) with two states and three neighborhoods that generate maximum cycle sequence which usually adapted as pseudo random number generator. However, the sequence is actually the permutation of finite elements which is suitable for the S-Box construction. Within this paper context, we manipulate the sequence by varying the initial condition to produce about 8192 different S-Box with different security level from 32 different rule combination. The maximum nonlinearity that we could achieve is 108 with differential uniformity value of 8. � BEIESP.

During the current mobile technology era, social media rumors (SMRs) propagate significantly faster, hence, are difficult to control. According to psychological research, SMR propagation can be better controlled with refutation. However, refutation must be timely, and supported with credible information. This is in line with the guideline provided in the Holy Quran, especially verse four of Surat An-Nisa, which urges people to refer to the leader or the authority to ascertain the veracity of new information concerning public security. This paper aims to review prominent prior psychology literature on rumor quelling strategies (RQS), and then maps them with solutions proposed by computer science research. We discovered that computer science studies in the related literature proposed noble solutions aligned with the ultimate goals in psychological research, including refutation. However, we suggest that these solutions be merged, and human intervention cannot be ignored, especially the verification process. Consequently, we identified six processes to be consolidated in a framework to further improve the refutation of SMRs. The six processes are: (1) filteration, (2) topic classification, (3) verifier identification, (4) notification to verifier, (5) verification, and (6) refutation. The identified steps act as the basis for subsequent research progress. � 2017 American Scientific Publishers All rights reserved.