The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.

    One of ciphering systems depends on transposition of letters in plain text to generate cipher text. The programming of transposition depends mainly on 2-dimension matrix in either methods but the difference is in columnar .We print columns in the matrix according to their numbers in key but in the fixed, the cipher text will be obtained by printing matrix by rows.

        People are comfortable with e-banking services, but they are exposed to a great deal of danger these days due to fraudulent acts such as password hacking and personal information theft. Everything individuals do online relies heavily on passwords. Using a password protects one's identity online, in forums, and through email. Online transactions are vulnerable to identity theft if they do not have a secure password. Internet users with critical statements are vulnerable to various assaults, including the theft and exploitation of user IDs and passwords. This paper introduces novel password encryption by fingerprint and a random number to make each password unique and robust against attacks, with a magnificent time elapsed o

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

In this paper, a method for data encryption was proposed using two secret keys, where the first one is a matrix of XOR's and NOT's gates (XN key), whereas the second key is a binary matrix (KEYB) key. XN and KEYB are (m*n) matrices where m is equal to n. Furthermore this paper proposed a strategy to generate secret keys (KEYBs) using the concept of the LFSR method (Linear Feedback Shift Registers) depending on a secret start point (third secret key s-key). The proposed method will be named as X.K.N. (X.K.N) is a type of symmetric encryption and it will deal with the data as a set of blocks in its preprocessing and then encrypt the binary data in a case of stream cipher.

  Speech is the first invented way of communication that human used age before the invention of writing. In this paper, proposed method for speech analyses to extract features by using multiwavelet Transform (Repeated Row Preprocessing).The proposed system depends on the Euclidian differences of the coefficients of the multiwavelet Transform to determine the beast features of speech recognition. Each sample value in the reference file is computed by taking the average value of four samples for the same data (four speakers for the same phoneme). The result of the input data to every frame value in the reference file using the Euclidian distance to determine the frame with the minimum distance is said to be the "Best Match". Simulatio

In this work , a hybrid scheme tor Arabic speech for the recognition

of  the speaker  verification  is presented  . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural  network has been used as a recognizer  tor speaker verification after extract spectral  features from an acoustic signal  by Fast Fourier Transformation Algorithm(FFT) .

The system was im plemented using a PENTIUM  processor , I000

MHZ compatible and MS-dos 6.2 .

Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8

     Theoretically, an eight-term chaos system is presented. The effect of changing the initial conditions values on behavior Chen system was studied. The basic dynamical properties of system are analyzed like time series, attractor, FFT spectrum, and bifurcation. Where the system appears steady state behavior at initial condition x_{i ,} y_i , z_i equal (0, 0, 0) respectively and it convert to quasi-chaotic at x_i ,y_i ,z_i  equal (-0.1, 0.5,-0.6). Finally, the system become hyper chaotic at x_i ,y_i ,z_i equal(-0.5, 0.5,-0.6 ) that can used it in many applications like secure communication.