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Predicting all star player in the national basketball association using random forest
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
Browsers fingerprinting motives, methods, and countermeasures
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
SigPloit: A New Signaling Exploitation Framework
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
Malicious VBScript detection algorithm based on data-mining techniques
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
Correlation between protocol selection and packet drop attack severity in ad hoc networks
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
A New Web Deception System Framework
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
Internet of Things security framework
For the past decade, Internet of Things (IoT) had an important role in our lives. It connects a large number of embedded devices. These devices fulfill very difficult and complicated tasks, which facilitate our work. Till now the security of IoT faces many challenges such as privacy, authentication, confidentiality, trust, middleware security, mobile security and policy enforcement. In order to
A computed tomography-based planning tool for predicting difficulty of minimally invasive aortic valve replacement
OBJECTIVES Minimally invasive aortic valve replacement has proven its value over the last decade by its significant advancement and reduction in mortality, morbidity and admission time. However, minimally invasive aortic valve replacement is associated with some on-site difficulties such as limited aortic annulus exposure. Currently, computed tomography scans are used to evaluate the anatomical
NU-Net: Deep residual wide field of view convolutional neural network for semantic segmentation
Semantic Segmentation of satellite images is one of the most challenging problems in computer vision as it requires a model capable of capturing both local and global information at each pixel. Current state of the art methods are based on Fully Convolutional Neural Networks (FCNN) with mostly two main components: an encoder which is a pretrained classification model that gradually reduces the
Behaviorally-Based Textual Similarity Engine for Matching Job-Seekers with Jobs
Understanding both of job-seekers and employers behavior in addition to analyzing the text of job-seekers and job profiles are two important missions for the e-recruitment industry. They are important tasks for matching job-seekers with jobs to find the top relevant suggestions for each job-seeker. Recommender systems, information retrieval and text mining are originally targeted to assist users