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A novel image steganography technique based on quantum substitution boxes

Substitution boxes play an essential role in designing secure cryptosystems. With the evolution of quantum technologies, current data security mechanisms may be broken due to their construction based on mathematical computation. Quantum walks, a universal quantum computational model, play an essential role in designing quantum algorithms. We utilize the benefits of quantum walks to present a novel technique for constructing substitution boxes (S-boxes) based on quantum walks (QWs). The performance of the presented QWs S-box technique is evaluated by S-box evaluation criteria, and our results

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Corneal Biomechanics Assessment Using High Frequency Ultrasound B-Mode Imaging

Assessment of corneal biomechanics for pre- and post-refractive surgery is of great clinical importance. Corneal biomechanics affect vision quality of human eye. Many factors affect corneal biomechanics such as, age, corneal diseases and corneal refractive surgery. There is a need for non-invasive in-vivo measurement of corneal biomechanics due to corneal shape preserving as opposed to ex-vivo measurements that destructs corneal tissue. In this study, a new approach for assessing corneal biomechanics in-vivo non-invasively using ultrasound estimation method with 100 KHz frame rate is proposed

Artificial Intelligence

Cyber Threats and Policies for Industrial Control Systems

Modern Industrial Control Systems (ICS) are very important in our life as we use information and communication technology (ICT) to manage, monitor and improve ICS usage. This continually exposes it to new threats due to the vulnerabilities and architectural weaknesses introduced by the extensive use of ICT. Different types of ICSs have common attacks in which these attacks are very sophisticated and have a great impact. This paper presents the results of our research on the impact of ICT attacks. Besides, it discusses how to protect ICS from attacks and policies/standards that each nation

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A Novel Vehicle Detection System

Histogram of oriented gradient (HOG) feature has been widely used in vehicle detection. In this paper, a modified version of HOG is proposed by introducing compass gradient into the HOG calculation. Three different versions of the modified HOG features are used as an input for linear and nonlinear support vector machine (SVM). The modified HOG variants proved to have better classification performance than that of the standard HOG. The classification results of modified HOG and nonlinear SVM are compared to the classification results of YOLO object detector. Finally, a vehicle detection system

Artificial Intelligence

VAFLE: Visual analytics of firewall log events

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

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Towards efficient and secure cloud

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

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Enabling cloud business by QoS roadmap

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

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Enhanced customer churn prediction using social network analysis

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

Artificial Intelligence

A Universal Model for Defective Classes Prediction Using Different Object-Oriented Metrics Suites

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

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Using Molecular Fingerprints as Descriptors in Toxicity Prediction: A Survey

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

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