Attacking the linear congruential generator on elliptic curves via lattice techniques

In this paper we study the linear congruential generator on elliptic curves from the cryptographic point of view. We show that if sufficiently many of the most significant bits of the composer and of three consecutive values of the sequence are given, then one can recover the seed and the composer (even in the case where the elliptic curve is private). The results are based on lattice reduction techniques and improve some recent approaches of the same security problem. We also estimate limits of some heuristic approaches, which still remain much weaker than those known for nonlinear congruential generators. Several examples are tested using implementations of ours algorithms.

Co-simulation of linear congruential generator by using Xilinx system generator and MATLAB Simulink

<p>Arbitrary numerals are utilized in a wide range of uses. Genuine arbitrary numeral generators are moderate and costly for some applications while pseudo arbitrary numeral generators (RNG) do the trick for most applications. This paper fundamentally concentrates around the co-simulation of the linear congruential generator (LCG) model utilizing the Xilinx System generator and checking on Matlab Simulink. The design is obtained from the LCG calculation offered by Lehmer. Word lengths decrease strategy has been utilized to streamline the circuit. Simulation has been done effectively. The effective N bit LCG is structured and tried by utilizing demonstrating in MatLab Simulink. The Co-simulation of the model is done by utilizing the Xilinx system generator. This paper conducts an exhaustive search for the best arbitrary numeral generator in a full period linear congruential generator (LCG) with the largest prime numbers.</p>

An Efficient Machine Learning Based Image Encryption Scheme for Medical Image Security

Medical images are very important in most of the application than any other images. In real time applications like telemedicine application, communication of medical image through open access needs protection as well as security at high level. Many imaging information has its own unique features which are so difficult to analyse and make decision to identify necessary techniques for protecting confidential image of unauthenticated access, Utmost all the existing encryption algorithms are mainly concentrating on textual data, but for multimedia data like images, it is not suitable. The main contribution done in this work is for ensuring increased security level over medical images regardless of presence of noises. In this algorithm, DNA subsequence operations combining with the use of improved Combined Linear Congruential Generator (C-LCG) were used for encryption of information. This paper discuss the idea of the improvement of safe and secure techniques using machine learning which is justified by the entropy value and correlation among adjacent pixels with performance parameters. The original image was scrambled using Combined Linear Congruential Generator with Bit rotation operation (BRO) and then image is transformed by effective encryption method using DNA subsequence operations. The proposed scheme discloses the correlation between pixel and entropy. Experimentation results showed that correlation among pixels is reduced while maximizing entropy. Number of Pixel Change Rate (NPCR) and Peak signal to noise (PSNR) ratio were also been analysed. In proposed algorithm, maximum NPCR values is achieved which shows the scattering of pixels in Encrypted image is high. PSNR shows a better encryption quality with lower the values.

Implementasi Metode Linear Congruential Generator pada Game Puzzle Kesenian Tari

Kesenian tari adalah cabang kesenian nusantara yang menggunakan gerakan tubuh dan diperagakan secara berirama yang bertujuan untuk mengekspresikan perasaan atau menyampaikan pesan individu atau kelompok. Pada aplikasi puzzle ini pengguna diberi dua pilihan level yaitu 2x3 dan 3x3. Game puzzle ini bertemakan Kesenian Tari di Pulau Jawa yang ditujukan untuk anak-anak berusia 6-10 tahun. Di dalam aplikasi game ini terdapat beberapa gambar dari berbagai provinsi di pulau jawa yang telah diubah kedalam tampilan puzzle yang nantinya pengguna dapat menyusun potongan gambar tersebut. Perancangan ini menerapkan metode Linear Congruential Generator (LCG) sebagai pengacak gambar yang disajikan pada aplikasi ini. Berdasarkan hasil pengujian didapatkan bahwa aplikasi ini berjalan sesuai dengan konsep awal dan penerapan metode berhasil diterapkan.

APLIKASI PENGENALAN HURUF DAN ANGKA, WARNA, SAYURAN DAN BUAH-BUAHAN UNTUK ANAK PAUD BERBASIS SMARTPHONE MENGGUNAKAN METODE LINEAR CONGRUENT(LCM)

Dunia anak adalah dunia bermain dan bergembira oleh karena itu masa emas bagi mereka jang anlah dibebani dengan hal-hal yang berat membani tumbuh kembang mereka oleh sebab ini jangan mereka dibebani dengan kurikulum belajar dan tugas-tugas yang menghabiskan waktu mereka. Faktor fisikologis orang tua yag mendapat pendidikan yang keras dan keinginan besar mereka agar anak-anaknya mengikuti apa yang menjadi kehendak orang tua maka dibebani dan mendapat tekanan untuk memperoleh hasil yang sempurna dengan cara memasukkan anak-anaknya ke di bimbingan belajar, Lembaga Pendidikan Anak Usia Dini (PAUD) karena prinsip mereka bahwa prestasi menunjukan keberhasilan orang tuanya khususnya anak di usia dini. Metode Linear Congruent(LCM) merupakan jenis PRNG yang banyak digunakan dalam aplikasi komputer modern, ditemukan oleh D.H Lehmer, Metode ini memanfaatkan model linier untuk membangkitkan bilangan acak Hasil Pengujian Metode Linear Congruent(LCM) ini Mudah dipelajari dan di implementasikan, selain itu dapat diterapkan pada aplikasi simulasi lain karena algoritma ini kecepatannya yang baik sangat efisien secara waktu proses, Adanya proses shuffling, membantu mengatasi masalah Linear Congruential Generator (LCG) pada properti independent (kebergantungan dari bilangan yang muncul berurutan), karena bilangan yang dihasilkan diacak posisinya. Kata Kunci: Dunia Anak, Belajar, Metode Linear Congruent, Algoritma

A Hybrid Inversive Congruential Pseudorandom Number Generator with High Period

Though generating a sequence of pseudorandom numbers by linear methods (Lehmer generator) displays acceptable behavior under some conditions of the parameters, it also has undesirable features, which makes the sequence unusable for various stochastic simulations. An extension which showed promise for such applications is a generator obtained by using a first-order recurrence based upon the inversive modulo a prime or a prime power, called inversive congruential generator (ICG). A lot of work has been dedicated to investigate the periods (under some conditions of the parameters), the lattice test passing, discrepancy and other statistical properties of such a generator. Here, we propose a new method, which we call hybrid inversive congruential generator (HICG), based upon a second order recurrence using the inversive modulo $M$, a power of 2. We investigate the period of this pseudorandom numbers generator (PRNG) and give necessary and sufficient conditions for our PRNG to have periods $M$ (thereby doubling the period of the classical ICG) and $M/2$ (matching the one of the ICG). Moreover, we show that the lattice test complexity for a binary sequence associated to (a full period) HICG is precisely M/2.