With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

A new data for Fusion power density has been obtained for T-3He and T-T fusion reactions, power density is a substantial term in the researches related to the fusion energy generation and ignition calculations of magnetic confined systems. In the current work, thermal nuclear reactivities, power densities of a fusion reactors and the ignition condition inquiry are achieved by using a new and accurate formula of cross section, the maximum values of fusion power density for T-3He and TT reaction are 1.1×107 W/m3 at T=700 KeV and 4.7×106 W/m3 at T=500 KeV respectively, While Zeff suggested to be 1.44 for the two reactions. Bremsstrahlung radiation has also been determined to reaching self- sustaining reactors, Bremsstrahlung values are 4.5×

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

A sensitive and selective method have been developed for the determination of palladium (II)and platinum (II) . A new reagent and two complexes have been prepared in ethanolic solutions .The method is based on the chelation of metal ions with 4-(4?- pyrazolon azo) resorcinol (APAR) to form intense color soluble products, that are stable and have a maximum absorption at 595 nm and at 463 nm and ?max of 1.11×10 4 and.1.35 ×104 Lmole-1cm-1 for Pd(II) Pt(II) respectively. A linear correlation of (1.4 – 0.2) and (3.2 -0.4 ) ppm for pd(II) pt(II) respectively .The stability constants , relative errors , a relative standard deviations for Pd(II) and Pt(II) were 0.40×105 , 0.4×104 L mol-1 ,0.34 - 0.21% and 2.4 – 0.91% respectively.

Results of exposure larvae of the most important predator in the integrated pest management , the green lacewings, Chrysoperla carnea (Stephens) to various densities of fig moth Ephestia cautella eggs showed increasing in the number of consumed prey at decreasing rate of increasing prey density where curve slope consumption decreased gradually until leveling off. These specifications concurred with type II functional response that predators appear towards varied densities of its preys ,that was confirm by logistic regression between the proportion of prey eaten in relation to prey offered . Third larval instars of the predator showed attack rate (a) of 4.85. This was greater than the second larval instar (3.58). Handling time (Th) per