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Designing a New Text Encryption Approach Based on Genetic Algorithm
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Today, data security is a major problem concerning organizations and indi- viduals. The confidentiality of information is associated with using reliable and robust encryption algorithms in systems. Cyber-attacks on data and systems have become prevalent and sophisticated, and are increasing rapidly; hence, the need for developing robust encryption algorithms is crucial nowadays. This paper proposes a new encryption algorithm using dynamic symmetric key cryptography to encrypt text files. It utilizes a secret key for encryption and decryption processes, where the key’s length is varied depending on the text size. This presented approach gives a trade-off between speed and security, making it suitable for various applications, such as secure messages and files. It utilizes the Genetic Algorithm (GA) only for creating a robust key, which re- duces the complexity and computation overheads. The robustness and effectiveness of the proposed encryption algorithm were evaluated thoroughly by implementing several analysis tests, such as entropy, correlation, and the avalanche effect. The results of these tests demonstrate high randomness and uniformity in the created ciphertext and provide an important contribution to the enhancement of the cryptography field for protecting data.

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Nonparametric Binary Logistic Regression
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In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro

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