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Article
A Modified Similarity Measure for Improving Accuracy of User-Based Collaborative Filtering

Authors: Nadia F. AL-Bakri --- Soukaena H. Hashim
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2018 Volume: 59 Issue: 2B Pages: 934-945
Publisher: Baghdad University جامعة بغداد

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Abstract

Production sites suffer from idle in marketing of their products because of the lack in the efficient systems that analyze and track the evaluation of customers to products; therefore some products remain untargeted despite their good quality. This research aims to build a modest model intended to take two aspects into considerations. The first aspect is diagnosing dependable users on the site depending on the number of products evaluated and the user's positive impact on rating. The second aspect is diagnosing products with low weights (unknown) to be generated and recommended to users depending on logarithm equation and the number of co-rated users. Collaborative filtering is one of the most knowledge discovery techniques used positively in recommendation system. Similarity measures are the core operations in collaborative filtering; however, there is a certain deviance through using traditional similarity measures, which decreases the recommendation accuracy. Thus, the proposed model consists of a combination of measures: constraint Pearson correlation, jaccard distance measure and inverse user frequency (IUF). The experimental results implemented on movielens data set using MATLAB show a comparison between the results of the proposed model and some of the traditional similarity measures. The outcome results of the comparison show that the proposed model can be used as a parameter in the prediction process to achieve accurate prediction results during recommendation process


Article
Intrusion Detection System Based on Data Mining Techniques to Reduce False Alarm Rate

Authors: Sarah M. Shareef --- Soukaena H. Hashim
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 2 Part (B) Engineering Pages: 110-119
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Nowadays, Security of network traffic is becoming a major issue ofcomputer network system according to the huge development of internet.Intrusion detection system has been used for discovering intrusion and tomaintain the security information from attacks. In this paper, produced twolevels of mining algorithms to construct Network Intrusion Detection System(NIDS) and to reduce false alarm rate, in the first level Naïve Bayes algorithmis used to classify abnormal activity into the main four attack types fromnormal behavior. In the second level ID3 decision tree algorithm is used toclassify four attack types into (22) children of attacks from normal behavior.To evaluate the performance of the two proposed algorithms by using kdd99dataset intrusion detection system and the evaluation metric accuracy,precision, DR, F-measure. The experimental results prove that the proposalsystem done high detection rates (DR) of 99 % and reduce false positives (FP)of 0 % for different types of network intrusions


Article
Propose Multi level Network Intrusion Detection System to detect intrusion in Cloud Environment
اقتراح نظام كشف تطفل شبكي متعدد المستوى لكشف التسلل في بيئة الحوسبة السحابية

Authors: Shawq malik Mehibes شوق مالك محيبس --- Soukaena H. Hashim سكينة حسن هاشم
Journal: AL-MANSOUR JOURNAL مجلة المنصور ISSN: 18196489 Year: 2018 Issue: 29 Pages: 41-61
Publisher: Private Mansour college كلية المنصور الاهلية

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Abstract

Cloud computing is one of the popular technologies, which can used by most organizations because of its attractive properties such as availability, flexibility, integrity. The open and distributed structure of Cloud Computing and the services provided by it make it attractive aim for potential cyber-attacks by intruders. Network intrusion detection system (NIDS) represents important security mechanism, provides defence layer which monitors network traffic to detect suspicious activity and policy violations. This work proposed Multi-level-NIDS to detect intrusions and the type of intrusion in traditional/Cloud network. The proposed system evaluated with kdd99 dataset, the experimental results shows the efficiency and capability of the proposed system in detect attack and type of attack.

الحوسبة السحابية هي واحدة من التقنيات الشائعة،التي تستخدم في معظم المؤسسات لما لها من خصائص مميزة مثل التوافر، المرونة ، التكامل. لهيكلية المفتوحة والموزعة للحوسبة السحابية والخدمات المقدمة جعلتها هدف محبب للهجمات الالكترونية المحتملة. نظام كشف التطفل الشبكي (NIDS) يمثل الية امنية مهمة،توفر طبقة دفاعية التي تراقب حركة مرور الشبكة للكشف عن نشاطات مشبوهة او انتهاك للسياسات. هذا العمل يقترح نظام كشف تطفل شبكي متعدد المستوى لكشف التطفل ونوع التطفل في الشبكة التقليدية / السحابية. النظام المقترح قيم باستخدام مجموعة البيانات القياسية KDD99، النتائج التجريبية اظهرت كفاءة وقدرة النظام المقترح في كشف الهجوم ونوع الهجوم

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