An optimal transportation routing approach using GIS-based dynamic traffic flows

This paper examines the value of real-time traffic information gathered through Geographic Information Systems for achieving an optimal vehicle routing within a dynamically stochastic transportation network. We present a systematic approach in determining the dynamically varying parameters and implementation attributes that were used for the development of a Web-based transportation routing application integrated with real-time GIS services. We propose and implement an optimal routing algorithm by modifying Dijkstra’s algorithm in order to incorporate stochastically changing traffic flows. We describe the significant features of our Web application in making use of the real-time dynamic traffic flow information from GIS services towards achieving total costs savings and vehicle usage reduction. These features help users and vehicle drivers in improving their service levels and productivity as the Web application enables them to interactively find the optimal path and in identifying destinations effectively

Using response action with Intelligent Intrusion detection and prevention System against web application malware

Findings: After evaluating the new system, a better result was generated in line with detection efficiency and the false alarm rate. This demonstrates the value of direct response action in an intrusion detection system

Machine learning based botnet identification traffic

The continued growth of the Internet has resulted in the increasing sophistication of toolkit and methods to conduct computer attacks and intrusions that are easy to use and publicly available to download, such as Zeus botnet toolkit. Botnets are responsible for many cyber-attacks, such as spam, distributed denial-of-service (DDoS), identity theft, and phishing. Most of existence botnet toolkits release updates for new features, development and support. This presents challenges in the detection and prevention of bots. Current botnet detection approaches mostly ineffective as botnets change their Command and Control (C&C) server structures, centralized (e.g., IRC, HTTP), distributed (e.g., P2P), and encryption deterrent. In this paper, based on real world data sets we present our preliminary research on predicting the new bots before they launch their attack. We propose a rich set of features of network traffic using Classification of Network Information Flow Analysis (CONIFA) framework to capture regularities in C&C communication channels and malicious traffic. We present a case study of applying the approach to a popular botnet toolkit, Zeus. The experimental evaluation suggest that it is possible to detect effectively botnets during the botnet C&C communication generated from new updated Zeus botnet toolkit by building the classifier using machine learning from an earlier version and before they launch their attacks using traffic behaviors. Also, show that there is similarity in C&C structures various Botnet toolkit versions and that the network characteristics of botnet C&C traffic is different from legitimate network traffic. Such methods could reduce many different resources needed to identify C&C communication channels and malicious traffic

From ZeuS to Zitmo : trends in banking malware

In the crimeware world, financial botnets are a global threat to banking organizations. Such malware purposely performs financial fraud and steals critical information from clients' computers. A common example of banking malware is the ZeuS botnet. Recently, variants of this malware have targeted mobile platforms, as The-ZeuS-in-the-Mobile or Zitmo. With the rise in mobile systems, platform security is becoming a major concern across the mobile world, with rising incidence of compromising Android devices. In similar vein, there have been mobile botnet attacks on iPhones, Blackberry and Symbian devices. In this setting, we report on trends and developments of ZeuS and its variants

WHY STAY? SAUDI WOMEN’S ADAPTIONS TO VIOLENCE

The study investigates the reasons why women continue to live with an abusive husband and examines the relationship between their reasons and a number of variables that support one’s ability to cope with spousal violence. These variables include employment status, educational level, number of children, marriage duration, the social status of the wife's family and the number of violent incidents. A demographic survey and a spousal violence adaption scale were administered to a sample of 114 abused wives. The results revealed that all of the variables and several of the dimensions represented by the violence adaption scale affected the women’s decisions. The impact of these variables was more obvious among nonworking wives and the lesser educated, women with a greater number of children, those who had been married longer, those who senatal families had a low social status, and those who were subjected to violence more frequently. Keywords: adaptation to violence, marital violence, Saudi Arabia, spousal violence, violence against women in Saudi Arabia, why women stay in violent relationships

Intelligent mobile malware detection using permission requests and API calls

Malware is a serious threat that has been used to target mobile devices since its inception. Two types of mobile malware attacks are standalone: fraudulent mobile apps and injected malicious apps. Defending against the cyber threats of mobile malware requires a strong understanding of the permissions declared in applications and application programmeinterface (API) calls. In this paper, we propose an effective classification model that combines permission requests and API calls. As Android apps use a large number of APIs, we propose three different grouping strategies for choosing the most valuable API calls to maximize the likelihood of identifying Android malware apps: the ambiguous group, risky group, and disruptive group. The results demonstrate that compared with benign apps, malicious applications invoke a different set of API calls and that mobile malware often requests dangerous permissions to access sensitive data more often than benign apps. Empirical results obtained with a real malware dataset containing 27,891 Android apps suggest that our proposed method is effective at detecting mobile malware apps and achieves an F-measure of 94.3%. Our model can significantly assist in the process of malware forensic investigation and mobile application analysis.acceptedVersion"© 2020. This is the authors’ accepted and refereed manuscript to the article. Locked until 5.2.2022 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

The Relationship between Moral Values and Social Acts from Max Weber's Perspective: An Empirical Study Based a Sample of Students from King Abdulaziz University

The present study aims to identify the relationship between moral values ??and social acts in light of Max Weber's theory of action in terms of some demographic variables (i.e., gender, place of residency, academic level, and academic specialization) of some college students. The study, however, subjected a sample consisting of 360 students at King Abdul Aziz University, Jeddah, Saudi Arabia. The study tools included demographic data form and two criteria of measurements: moral values ??and social act. The statistical calculations were implemented using Arithmetic Mean, Standard Deviation, T-test and Pearson correlation. The results revealed that the correlation and congruence between moral values ??and social acts are much clearer in the female sample than the male sample, and in rural inhabitants than the urban ones, and in the students of the college level (1-4) than the college level (5-8). Keywords : Moral Values, Social Action, Gender,  Residency, Grade, and Academic Specialization

Teaching Mathematics and Developing Students' Thinking Skills

تعد تنمية مهارات التفكير لدى الطلاب من أهم أهداف تعليم وتعلم الرياضيات، وتناول الورقة الحالية التفكير وكيفية تنميته، حيث تستعرض المقصود بالتفكير، وخصائصه ومكوناته الأساسية مثل (العزم والتصميم والمثابرة، والحد من التوتر والإثارة، والإصغاء للآخرين، والذكاء الاجتماعي، والمرونة في التفكير، وما وراء المعرفة، وتحري الدقة والصواب، وطرح السؤال وعرض المشكلة، والخبرة السابقة وتطبيقها في مواقف جديدة، وروح المغامرة)، وأهمية التفكير، وأساليب تنمية مهارات التفكير لدى الطلاب، والكفايات الأدائية اللازمة لمعلمي الرياضيات لتنمية مهارات التفكير لدى طلابهم، وكيفية إعداد المعلم وتدريبه فيما يتعلق بتنمية التفكير، وتتناول الحقائب التعليمية كأسلوب تدريبي لتنمية كفايات المعلم اللازمة لتنمية مهارات التفكير لدى طلابه. مع توضيح ذلك بحقيبة تعليمية متكاملة.Developing students' thinking skills is one of the most important goals of teaching and learning mathematics. The present paper reviews thinking and how to develop it. It examines the meaning of thinking, its characteristics and basic components such as determination, determination, perseverance, listening to others, social intelligence, flexibility in thinking, meta cognation, and the skills needed for mathematics teachers to develop students' thinking skills. And how teacher preparation and training with regard to the development of thinking, the paper presents educational modules as a way of training for developing teacher competences which needed to develop students' thinking skills. With an integrated educational modules