The advanced technology in the internet and social media, communication companies, health care records and cloud computing applications made the data around us increase dramatically every minute and continuously. These renewals big data involve sensitive information such as password, PIN number, credential numbers, secret identifications and etc. which require maintaining with some high secret procedures. The present paper involves proposing a secret multi-dimensional symmetric cipher with six dimensions as a cubic algorithm. The proposed algorithm works with the substitution permutation network (SPN) structure and supports a high processing data rate in six directions. The introduced algorithm includes six symmetry rounds transformations for encryption the plaintext, where each dimension represents an independent algorithm for big data manipulation. The proposed cipher deals with parallel encryption structures of the 128-bit data block for each dimension in order to handle large volumes of data. The submitted cipher compensates for six algorithms working simultaneously each with 128-bit according to various irreducible polynomials of order eight. The round transformation includes four main encryption stages where each stage with a cubic form of six dimensions.
Problem statement: Grammatical Relation (GR) can be defined as a linguistic relation established by grammar, where linguistic relation is an association among the linguistic forms or constituents. Fundamentally the GR determines grammatical behaviors such as: placement of a word in a clause, verb agreement and the passivity behavior. The GR of Arabic language is a necessary prerequisite for many natural language processing applications, such as machine translation and information retrieval. This study focuses on the GR related problems of Arabic language and addresses the issue with optimum solution. Approach: We had proposed a rule based production method to recognize Grammatical Relations (GRs), as the rule-based approach had been successfully used in developing many natural language processing systems. In order to eradicate the problems of sentence structure recognition, the proposed technique enhances the basic representations of Arabic language such as: Noun Phrase (NP), Verb Phrase (VP), Preposition Phrase (PP) and Adjective Phrase (AP). We had implemented and evaluated the Rule-Based approach that handles chunking and GRs of Arabic sentences. Results: The system was manually tested on 80 Arabic sentences, with the length of each sentence ranging from 3-20 words. The results had yielded the F-score of 83.60%. This outcome proves the viability of this approach for Arabic sentences of GRs extraction. Conclusion: The main achievement of this study is development of Arabic grammatical relation extractions based ob rule-based approaches.
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