In this work, we present VAFLE, an interactive network security visualization prototype for the analysis of firewall log events. Keeping it simple yet effective for analysts, we provide multiple coordinated interactive visualizations augmented with clustering capabilities customized to support anomaly detection and cyber situation awareness. We evaluate the usefulness of the prototype in a use case with network traffic datasets from previous VAST Challenges, illustrating its effectiveness at promoting fast and well-informed decisions. We explain how a security analyst may spot suspicious

Cloud computing is becoming more and more popular. It is increasing in popularity with companies as it enables them to share various resources in a cost effective way. Cloud computing has lots of advantages, however some issues need to be handled before organizations and individuals have the confidence to rely on it. Security and privacy are at the forefront of these important issues. In this paper, the evolution of cloud computing along with its deployment and delivery models are highlighted. Also, the difference between cloud computing and other deployment models are discussed. We present

Day after day, global economy becomes tougher. It is a fact in which Cloud Computing business gets impacted the most. When it comes to cost, Cloud Computing is the most attractive paradigm for IT solutions. It is because Cloud Computing relaxes cost constraints. This relaxing enables Cloud Customers to operate their business through Cloud Computing under such economic pressure. On the other side, Cloud Computing solutions should deliver IT services at the agreed and acceptable Quality of Service levels. This moves the economic challenges from Cloud Customer premises to Cloud Provider premises

There were 6.8 billion estimates for mobile subscriptions worldwide by end of 2013 [11]. As the mobile market gets saturated, it becomes harder for telecom providers to acquire new customers, and makes it essential for them to retain their own. Due to the high competition between different telecom providers and the ability of customers to move from one provider to another, all telecom service providers suffer from customer churn. As a result, churn prediction has become one of the main telecom challenges. The primary goal of churn prediction is to predict a list of potential churners, so that

Recently, research studies were directed to the construction of a universal defect prediction model. Such models are trained using different projects to have enough training data and be generic. One of the main challenges in the construction of a universal model is the different distributions of metrics in various projects. In this study, we aim to build a universal defect prediction model to predict software defective classes. We also aim to validate the Object-Oriented Cognitive Complexity metrics suite (CC metrics) for its association with fault-proneness. Finally, this study aims to

During humans' lifetime, their bodies deal with different chemicals through various sources. Chemical toxicity is a challenging problem that needs rapid and efficient methods for evaluation of environmental chemicals, or medications development. Computer science helps in toxicity prediction through building models from pre-tested compounds by learning from data. These models raise a flag to avoid trying some combinations for trial in wet-lab, which reduces the high cost of clinical trials. A compound chemical structure features are represented by Molecular Fingerprint. This survey searches for

In this paper, we report an effective cryptosystem aimed at securing the transmission of medical images in an Internet of Healthcare Things (IoHT) environment. This contribution investigates the dynamics of a 2-D trigonometric map designed using some well-known maps: Logistic-sine-cosine maps. Stability analysis reveals that the map has an infinite number of solutions. Lyapunov exponent, bifurcation diagram, and phase portrait are used to demonstrate the complex dynamic of the map. The sequences of the map are utilized to construct a robust cryptosystem. First, three sets of key streams are

Feature selection is an NP-hard combinatorial problem, in which the number of possible feature subsets increases exponentially with the number of features. In the case of large dimensionality, the goal of feature selection is to determine the smallest possible features considering the most informative subset. In this paper, we proposed a hybrid feature selection optimization model for Cancer Classification called, ENSVM. Our model is based on using the Elastic Net (EN) method that regulates and selects variables for gene selection of genomic microarray data. We applied three different

Both Big Data and Software-Defined Network have a significant impact in both academic and practical aspects. These two areas have been addressed separately, but both did not contribute to the same subset area of contribution. However, Big Data can greatly facilitate, improve, and have a great impact on Software Defined Network, and vice versa. In this paper, we show how SDN helps Big Data solve several issues regarding Big Data applications, including data processing in the data centers, data delivery and traffic monitoring. For Big Data, we also show how it can help SDN as well, including

At the time of writing, the COVID-19 pandemic is one of the lead causes of death worldwide and has caused significant changes to everyone's lives. While a vaccine is still unavailable, early screenings and detection of the disease can significantly help in managing the healthcare system's capacity as well as allow radiologists and clinicians better assign their priorities. With deep learning's rapid advancements over the last few years, its application in solving this issue is only natural. This paper aims to outline the works of a few major developments in the field of using deep learning to