Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

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

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat

This work describes, selenium (Se) films were deposited on clean glass substrates by dc planar magnetron sputtering technique.The dependence of sputtering deposition rate of Se film deposited on pressure and DC power has been studied. The optimum argon pressure has range (4x10-1 -8x10-2 )mbar. The optical properties such as absorption coefficient (α) was determined using the absorbance and transmission measurement from UnicoUV-2102 PC spectrophotometer, at normal incidence of light in the wavelength range of 200-850 nm. And also we calculated optical constants(refractive index (n), dielectric constant (εi,r), and Extinction coefficient (κ) for selenium films.

      Wireless sensor network (WSN) security is an important component for protecting data from an attacker. For improving security, cryptography technologies are divided into two kinds: symmetric and asymmetric. Therefore, the implementation of protocols for generating a secret key takes a long time in comparison to the sensor’s limitations, which  decrease network throughput because they are based on an asymmetric method. The asymmetric algorithms are complex and decrease network throughput. In this paper, an encryption symmetric secret key in wireless sensor networks (WSN) is proposed. In this work, 24 experiments are proposed, which are encryption using the AES algorithm in the cases of 1 key, 10 keys, 25 keys, and 50 keys. I

Regarding the security of computer systems, the intrusion detection systems (IDSs) are essential components for the detection of attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in real time. A major drawback of the IDS is their inability to provide adequate sensitivity and accuracy, coupled with their failure in processing enormous data. The issue of classification time is greatly reduced with the IDS through feature selection. In this paper, a new feature selection algorithm based on Firefly Algorithm (FA) is proposed. In addition, the naïve bayesian classifier is used to discriminate attack behaviour from normal behaviour in the network tra

The V2O5 films were deposited on glass substrates which produce using "radio frequency (RF)"power supply and Argon gas technique. The optical properties were investigated by, UV spectroscopy at "radio frequency" (RF) power ranging from 75 - 150 Watt and gas pressure, (0.03, 0.05 and 0.007 Torr), and substrate temperature (359, 373,473 and 573) K. The UV-Visible analysis shows that the average transmittance of all films in the range 40-65 %. When the thickness has been increased the transhumance was decreased from (65-40) %. The values of energy band gap were lowered from (3.02-2.9 eV) with the increase of thickness the films in relation to an increase in power, The energy gap decreased (2.8 - 2.7) eV with an increase in the pressure and