The Increasing number of mobiles and handheld devices that allow wireless access to enterprise data and services is considered a major concern for network designers, implementers and analysts. Enhancements of wireless technologies also accelerate the adoptions of enterprise wireless networks that are widely deployed solely or as an extension to existing wired networks. Bring Your Own Device is an

Research addressing Sentiment Analysis has witnessed great attention over the last decade especially after the huge increase in social media networks usage. Social networks like Facebook and Twitter generate an incredible amount of data on a daily basis, containing posts that discuss all kinds of different topics ranging from sports and products to politics and current events. Since data generated

In this paper, we investigate the problem of recognizing entities which are targeted by text sentiment in Arabic tweets. To do so, we train a bidirectional LSTM deep neural network with conditional random fields as a classification layer on top of the network to discover the features of this specific set of entities and extract them from Arabic tweets. We’ve evaluated the network performance

Emotion detection in Arabic text is an emerging research area, but the efforts in this new field have been hindered by the very limited availability of Arabic datasets annotated with emotions. In this paper, we review work that has been carried out in the area of emotion analysis in Arabic text. We then present an Arabic tweet dataset that we have built to serve this task. The efforts and

National Basketball Association (NBA) All Star Game is a demonstration game played between the selected Western and Eastern conference players. The selection of players for the NBA All Star game purely depends on votes. The fans and coaches vote for the players and decide who is going to make the All Star roster. A player who continues to receive enough votes in following years will play more All

With the continuous and aggressive competition in advertising businesses, uncontrollably desires have emerged to identify and classify consumers. It is proven that companies must have a clear definition of its target market. Based on this we have seen different ways to identify, analyze, and track consumers, either voluntarily or without their consent. Browser fingerprinting techniques have

Mobile communication networks are using signaling protocols to allow mobile users to communicate using short messages, phone calls and mobile data. Signaling protocols are also used to manage billing for operators and much more. The design flaws that signaling inherits made them vulnerable to attacks such as location tracking of subscriber, fraud, calls and SMS interception. With the high rate of

Malware attacks are amongst the most common security threats. Not only malware incidents are rapidly increasing, but also the attack methodologies are getting more complicated. Moreover malware writers expand in using different platforms and languages. This raises the need for new detection methods which support more reliable, low resource consuming and fast solutions. In this paper, a new

Mobile Ad hoc Network (MANET) are self-configuring, dynamic, networks that consist of nodes with various capabilities communicating through a wide spectrum of frequencies. Such flexibility in infrastructure and design comes with great risks in form of attacks on its nodes and the routing protocols that connect the network together. The aim of this paper is to explore the correlation between the

Web applications have many vulnerabilities that allow attackers to compromise sensitive data and gain unauthorized access to the production web servers. Compromised web-sessions represent a major threat. Current random attacks draw attention to the need for new protection and detection tools. In this paper, we propose a web deception scheme to mitigate web attacks in the production web site. The