An efficient stream cipher using Genetic Algorithm

Kumar, Ankit; Chatterjee, Kakali

doi:10.1109/wispnet.2016.7566557

Cited by 19 publications

(12 citation statements)

References 3 publications

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“…Different genetic algorithms were proposed to resolve this problem, as Jones and Beltramo's genetic algorithm, Falkenauer's one [5], and by 2000 William A.Green proposed a better one named Eager Breeder Greene [6]. Later, genetic and evolutionist algorithms were used in the design of cryptographic algorithms to reach better security like in [7][8][9][10][11]. In [3], [12], [13], and [14], Omary proposed an evolutionist-based encryption scheme and extended versions that aim to substitute the plaintext's characters to change their occurrence frequency.…”

Section: Related Workmentioning

confidence: 99%

Partition Ciphering System: A Difficult Problem Based Encryption Scheme

Ziani¹,

Omary²

2019

IJACSA

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In this article, a new encryption scheme called Partition Ciphering System is proposed to adapt and process the message according to the partition problem. The objective of this system, that can be applied as a standalone system or as a building block in a bigger system, is to achieve confidentiality, and maintain a balance between ones and zeros in the output so that attacks like frequency cryptanalysis is avoided and good entropy is met. At first, the authors describe the partition problem together with an adapted version. Secondly, the encryption and the decryption processes are provided. Next, a comparison, in terms of the statistical properties using the DIEHARDER battery, security analysis and performance, with other encryption schemes is presented. From the results, the proposed cryptosystem is resistant to frequency analysis and shows good entropy in the output. Moreover, compared to the Advanced Encryption Standard, it has a random behavior and good confusion and diffusion(Avalanche effect). Also, it displays better performance and resistance to brute force attack on the key.

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Section: Related Workmentioning

confidence: 99%

Partition Ciphering System: A Difficult Problem Based Encryption Scheme

Ziani¹,

Omary²

2019

IJACSA

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“…In Flipping of Bits one or more bits are converted into 0 to 1 or 1 to 0. In Boundary Mutation randomly upper or lower block in swapped in chromosome [9]. …”

Section: B Mutationmentioning

confidence: 99%

“…Ankit et al [9] generated the key for stream cipher with the help of natural selection process. The genetic operations were repeated until fitness value of any chromosome is less than threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

Implication of Genetic Algorithm in Cryptography to Enhance Security

Nazeer¹,

Mallah²,

Shaikh³

et al. 2018

ijacsa

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Abstract-In today's age of information technology secure transmission of information is a big challenge. Symmetric and asymmetric cryptosystems are not appropriate for high level of security. Modern hash function based systems are better than traditional systems but the complex algorithms of generating invertible functions are very time consuming. In traditional systems data is being encrypted with the key but still there are possibilities of eavesdrop the key and altered text. Therefore, key must be strong and unpredictable, so a method has been proposed which take the advantage of theory of natural selection. Genetic Algorithms are used to solve many problems by modeling simplified genetic processes and are considered as a class of optimization algorithms. By using Genetic Algorithm the strength of the key is improved that ultimately make the whole algorithm good enough. In the proposed method, data is encrypted by a number of steps. First, a key is generated through random number generator and by applying genetic operations. Next, data is diffused by genetic operators and then logical operators are performed between the diffused data and the key to encrypt the data. Finally, a comparative study has been carried out between our proposed method and two other cryptographic algorithms. It has been observed that the proposed algorithm has better results in terms of the key strength but is less computational efficient than other two.

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“…Reproduksi Proses menghasilkan keturunan individu di dalam populasi dilakukan dengan proses pindah silang dan proses mutasi. Proses pemilihan dua parent dari suatu populasi secara random atau proses pindah silang untuk menghasilkan kromosom baru disebut proses crossover (Kumar and Chatterjee, 2016). Sedangkan, proses mutasi merupakan proses menciptakan individu baru secara random (Zhou and Song, 2016).…”

Section: Siklus Algoritma Genetikaunclassified

Optimasi Derajat Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Diagnosis Penyakit Sapi Potong

Kurnianingtyas

Mahmudy

Widodo

2017

JTIIK

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AbstrakSistem inferensi fuzzy bisa digunakan untuk diagnosis penyakit pada sapi potong. Untuk mendapatkan akurasi yang tinggi maka batasan fungsi keanggotaan fuzzy perlu ditentukan secara tepat. Penggunaan metode logika fuzzy untuk memperoleh hasil diagnosis penyakit pada sapi potong sesuai pakar berdasarkan batasan gejala penyakit dan aturan-aturan yang diperoleh dari pakar. Batasan tersebut bisa diperbaiki menggunakan Algoritma Genetika untuk mendapatkan akurasi yang lebih baik. Pengujian yang dilakukan pada 51 data dari beberapa gejala penyakit menghasilkan akurasi sebesar 98,04% dengan menggunakan parameter genetika terbaik antara lain ukuran populasi sebesar 80, ukuran generasi sebesar 15, nilai Crossover rate (Cr) sebesar 0,9, dan nilai Mutation rate (Mr) sebesar 0,06. Akurasi tersebut mengalami peningkatan sebesar 3,54% sesudah dilakukannya optimasi pada metode logika fuzzy.

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An efficient stream cipher using Genetic Algorithm

Cited by 19 publications

References 3 publications

Partition Ciphering System: A Difficult Problem Based Encryption Scheme

Partition Ciphering System: A Difficult Problem Based Encryption Scheme

Implication of Genetic Algorithm in Cryptography to Enhance Security

Optimasi Derajat Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Diagnosis Penyakit Sapi Potong

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