Breast Cancer Diagnosis Using K-means ‎Methodology

يعد سرطان الثدي  المسبب الثاني للوفاة بين النساء بعد سرطان الرئة, و نظرا ً لخطورة هذا المرض، انبرت البحوث للمساعدة في تشخيص هذا المرض عن طريق تجهيز الطاقم الطبي بأنظمة تصنيف تعتمد على  الكمبيوتر لتحديد ما إذا كان المريض مصاب أم لا. يركز هذا البحث على طريقة استخدام (K-means) لتشخيص سرطان الثدي بالاعتماد على قاعدة بيانات عالمية معروفة باسم (WBCD) مخصصة لهذا النوع من الأبحاث. أثبتت هذه الطريقة فاعليتها في التصنيف وقد وصلت دقة النظام  الى96.4861٪.After lung cancer, breast cancer is the second cause of death among women. Due to the seriousness of the disease, research has stepped up to help diagnose this disease by providing medical personnel with a classification based computer systems that determine whether the patient is infected. This research focuses on the use method (K-means) for the diagnosis of breast cancer based on a global database known as (WBCD) dedicated to this purpose. The proposed method has proved its effectiveness in classification and the accuracy of the system is equal to 96.4861%

Key Generation for Vigenere Ciphering Based on Genetic Algorithm

Cryptography is a science securing of information. Encryption requires impregnable keys to encrypt or decrypt data these keys should be unpredictable and not easily to break. In this research we use genetic algorithm to generate keys for vigenere cipher. The best key is used to perform encryption. The keys created by genetic algorithm are tested for randomness by using the entropy test. The entropy calculation shows that randomness of key generated based on genetic processing is better than chosen key in the classical vigenere cipher

Review on Common Steganography Techniques

تحرص الجهات المختلفة على الحفاظ على سرية معلوماتها وحمايتها من الأطراف المتنافسة أو المعادية التي حرصت أيضًا على الوصول إلى تلك المعلومات بكافة الوسائل المتاحة. بما أن تشفير المعلومات ينكشف لأنه ينتج نصوصًا غير مفهومة تثير الشك، يميل البعض إلى العمل بطريقة تزيل الشكوك عن طريق إخفاء المعلومات في وسيط مثل النص أو الصورة بحيث يبدو ما يتم إرساله وتداوله طبيعيًا وخاليًا من العلامات أو رموز غير مفهومة كما لو لم يتم تحميلها بأي معلومات إضافية. هذا البحث يقدم مراجعة للتقنيات المستخدمة لإخفاء البيانات في الصور باعتبارها واحدة من أكثر تقنيات الإخفاء شيوعًا.Various authorities are keen to preserve the confidentiality of their information and protect it from competing or hostile parties who were also keen to access that information by all available means. Since the encryption of information is exposed as it produces incomprehensible texts that arouse suspicion, some tend to work in a way that removes suspicions by hiding the information in a medium like text or picture so that what is sent and circulated appears natural and free of signs or incomprehensible symbols as if not loaded with any additional information. This paper introduces a review the techniques used to hide data in images as one of the most common concealment techniques

Classification of medical datasets using back propagation neural network powered by genetic-based features elector

The classification is a one of the most indispensable domains in   the data mining and machine learning. The classification process has a good reputation in the area of diseases diagnosis by computer systems where the progress in smart technologies of computer can be invested in diagnosing various diseases based on data of real patients documented in databases. The paper introduced a methodology for diagnosing a set of diseases including two types of cancer (breast cancer and lung), two datasets for diabetes and heart attack. Back Propagation Neural Network plays the role of classifier. The performance of neural net is enhanced by using the genetic algorithm which provides the classifier with the optimal features to raise the classification rate to the highest possible. The system showed high efficiency in dealing with databases differs from each other in size, number of features and nature of the data and this is what the results illustrated, where the ratio of the classification reached to 100% in most datasets)

A new method for watermarking color images using virtual hiding and El-Gamal ciphering

One of the important issues in the era of computer networks and multimedia technology development is to find ways to maintain the reliability, credibility, copyright and non-duplication of digital content transmitted over the internet. For the purpose of protecting images from illegal usage, a watermark is used. A hidden digital watermark is the process of concealing information on a host to prove that this image is owned by a specific person or organization. In this paper, a new method has been proposed to use an RGB logo to protect color images from unlicensed trading. The method depends on retrieving logo data from specific locations in the host to form a logo when the owner claims the rights to those images. These positions are chosen because their pixels match the logo data. The locations of matching pixels are stored in a table that goes through two stages of treatment to ensure confidentiality: First, table compression, second, encoding positions in the compressed table through El-Gamal algorithm. Because the method depends on the idea of keeping host pixels without change, PSNR will always be infinity. After subjecting the host to five types of attack, the results demonstrate that the method can effectively protect the image and hidden logo is retrieved clearly even after the attacks