Hussam N. Fakhouri

Web Threats Detection and Prevention Framework

The rapid advancement in technology and the increased number of web applications with very short turnaround time caused an increased need for protection from vulnerabilities that grew due to decision makers overlooking the need to be protected from attackers or software developers lacking the skills and experience in writing secure code. Structured Query Language (SQL) Injection, cross-site scripting (XSS), Distributed Denial of service (DDos) and suspicious user behaviour are some of the common types of vulnerabilities in web applications by which the attacker can disclose the web application sensitive information such as credit card numbers and other confidential information. This paper proposes a framework for the detection and prevention of web threats (WTDPF) which is based on preventing the attacker from gaining access to confidential data by studying his behavior during the action of attack and taking preventive measures to reduce the risks of the attack and as well reduce the consequences of such malicious action. The framework consists of phases which begin with the input checking phase, signature based action component phase, alert and response phases. Additionally, the framework has a logging functionality to store and keep track of any action taking place and as well preserving information about the attacker IP address, date and time of the attack, type of the attack, and the mechanism the attacker used. Moreover, we provide experimental results for different kinds of attacks, and we illustrate the success of the proposed framework for dealing with and preventing malicious actions.

A Hybrid Methodology for Automation the Diagnosis of Leukemia Based on Quantitative and Morphological Feature Analysis

Recent year’s witnessed a huge revolution for developing an automated diagnosis for different disease such as cancer using medical image processing. Many researches have been dedicated to achieve this goal. Analyzing medical microscopic histology images provide us with large information about the status of patient and the progress of diseases, help to determine if the tissue have any pathological changes. Automation of the diagnosis of these images will lead to better, faster and enhanced diagnosis for different hematological and histological tissue images such as cancer. This paper propose an automated methodology for analyzing cancer histology and hematology microscopic images to detect leukemia using image processing by combining two diagnosis procedures initial and advance; the initial diagnosis depend on the percentage of the white blood cells in microscopic images affected by leukemia as indicator for the existence of leukemia in the blood smear sample. Whereas, the advance diagnosis classifying the leukemia according into different types using feature bag classifier. The experimental results showed that the proposed methodology initial diagnosis is able to detect leukemia images and differentiate it from samples that do not have leukemia. While, advance diagnosis it is able to detect and classify most leukemia types and differentiate between acute and chronic, but in some cases in the chronic leukemia where the percent of blast cells and shape are similar; it gave a diagnosis of the type of leukemia to the most similar type.

Website Search Engine Optimization: Geographical and Cultural Point of View

In this paper, we analyzed the influence of geographical area (Jordan) and a local culture on website search engine ranking, and identify the effect and the relationship of the local society keywords in increasing website ranking. Our analysis provides a foundation for understanding the search engine optimization in the local geographical area. In particular, it suggests that we could use social culture keywords to increase the website ranking in search engines that localize the search area such as Google.jo which localize the search for Jordan. The first part of the study started with the identification of keywords that were previously used by Jordanian users to search information related to Jordan prior to their interests. The frequently occurring keywords were then used to conduct the search engine ranking analysis in Jordan.