In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

      Landsat7 of Enhanced thematic mapper plus (ETM+) was launched on April 15,  1999. Four years later, images start degrading due to the scan line corrector (SLC). SLC is a malfunction that results in pixel gaps in images captured by the sensor of Landsat7. The pixel gap regions extend from about one pixel near the image center and reach up to about 14 pixels in width near the image edge. The shape of this loss is like a zigzag line; however, there are different studies about repairing these gaps. The challenge of all studies depends on retrieving inhomogeneous areas because the homogenous area can be retrieved quickly depending on the surrounding area. This research focuses on filling these gaps by utilizing pixels around them

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant

       The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

In recent years, the rapid development in the field of wireless technologies led to the appearance of a new topic, known as the Internet of things (IoT). The IoT applications can be found in various fields of our life, such as smart home, health care, smart building, and etc. In all these applications, the data collected from the real world are transmitted through the Internet; therefore, these data have become a target of many attacks and hackers. Hence, a secure communication must be provided to protect the transmitted data from unauthorized access. This paper focuses on designing a secure IoT system to protect the sensing data. In this system, the security is provided by the use of Lightweight AES encryption algorithm to encrypt the d

A new blind restoration algorithm is presented and shows high quality restoration. This
is done by enforcing Wiener filtering approach in the Fourier domains of the image and the
psf environments

Digital image started to including in various fields like, physics science, computer science, engineering science, chemistry science, biology science and medication science, to get from it some important information. But any images acquired by optical or electronic means is likely to be degraded by the sensing environment. In this paper, we will study and derive Iterative Tikhonov-Miller filter and Wiener filter by using criterion function. Then use the filters to restore the degraded image and show the Iterative Tikhonov-Miller filter has better performance when increasing the number of iteration To a certain limit then, the performs will be decrease. The performance of Iterative Tikhonov-Miller filter has better performance for less de

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained