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Real-world data mining problems require feature selection to improve efficiency and accuracy. Due to not considering characteristics of the FS problem itself, traditional mechanisms limit their performance on dealing with high-dimensional FS problems. Focused on it, this paper proposes a novel feature selection algorithm based on binary transient search optimization (TSO) with chaotic maps. Due to their pseudo-random behavior, chaotic systems can mimic randomness, which is essential for addressing complex problems through feature selection. In this methodology, the logistic equation is employed to generate periodic sequences of varying lengths within the TSO evolutionary algorithm. Experimental evaluations are conducted on 12 datasets from the UCI repository. On average, modified TSO improves classification accuracy by 15% over traditional methods across the datasets tested. Experimental results demonstrate that the proposed method has improved classification accuracy, diversity, and convergence, while removing redundancy. [ABSTRACT FROM AUTHOR]

In recent years, many chaotic image encryption algorithms have been cracked by chosen plaintext attack. Therefore, the method of associating the key with the plaintext to resist the cryptanalysis has received extensive attention from designers. This paper proposes a new method of cryptanalysis for image encryption algorithms with a key associated with plaintext. We broke an image encryption scheme using chaos and DNA encoding. Through our comprehensive security analysis, we found a security vulnerability in the mechanism of the association between the key and plaintext and proposed a breaking scheme. The experimental results show that the chosen plaintext attack can recover the cipher image to the plain image. The cryptanalysis scheme proposed in this paper can provide new ideas for subsequent cryptanalysis work and also provide some meaningful references for designers to improve the security of encryption algorithms when designing them. In addition, we also propose an improved logistic chaotic map with random bit-position scrambling. The improved chaotic map has a wider parameter range and a larger Lyapunov exponent. In the end, some suggestions are given to improve the original algorithm to resist such attacks. [ABSTRACT FROM AUTHOR]