Review on Malware and Malware Detection ‎Using Data Mining Techniques

البرمجيات الخبيثة هي اي نوع من البرمجيات او شفرات برمجية التي هدفها سرقة بعض المعلومات الخاصة او بيانات من نظام الكمبيوتر او عمليات الكمبيوتر او(و) فقط ببساطة لعمل المبتغيات غير المشروعة لصانع البرامجيات الخبيثة على نظام الكمبيوتر، وبدون الرخصة من مستخدمي الكمبيوتر. البرامجيات الخبيثة للمختصر القصير تعرف كملور. ومع ذلك، اكتشاف البرامجبات الخبيثة اصبحت واحدة من اهم المشاكل في مجال امن الكمبيوتر وذلك لان بنية الاتصال الحالية غير حصينه للاختراق من قبل عدة انواع من استراتيجيات الاصابات والهجومات للبرامجيات الخبيثة. فضلا على ذلك، البرامجيات الخبيثة متنوعة ومختلفة في المقدار والنوعيات وهذا يبطل بصورة تامة فعالية طرق الحماية القديمة والتقليدية مثل طريقة التواقيع والتي تكون غير قادرة على اكتشاف البرامجيات الخبيثة الجديدة. من ناحية أخرى، هذا الضعف سوف يودي الى نجاح اختراق (والهجوم) نظام الكمبيوتر بالإضافة الى نجاح هجومات أكثر تطوراً مثل هجوم منع الخدمة الموزع. طرق تنقيب البيانات يمكن ان تستخدم لتغلب على القصور في طريقة التواقيع لاكتشاف البرامجيات الخبيثة غير المعروفة. هذا البحث يقدم نظره عامة عن البرامجيات الخبيثة وانظمة اكتشاف البرامجيات الخبيثة باستخدام التقنيات الحديثة مثل تقنيات طريقة تعدين البيانات لاكتشاف عينات البرامجيات الخبيثة المعروفة وغير المعروفة.Malicious software is any type of software or codes which hooks some: private information, data from the computer system, computer operations or(and) merely just to do malicious goals of the author on the computer system, without permission of the computer users. (The short abbreviation of malicious software is Malware). However, the detection of malware has become one of biggest issues in the computer security field because of the current communication infrastructures are vulnerable to penetration from many types of malware infection strategies and attacks.  Moreover, malwares are variant and diverse in volume and types and that strictly explode the effectiveness of traditional defense methods like signature approach, which is unable to detect a new malware. However, this vulnerability will lead to a successful computer system penetration (and attack) as well as success of more advanced attacks like distributed denial of service (DDoS) attack. Data mining methods can be used to overcome limitation of signature-based techniques to detect the zero-day malware. This paper provides an overview of malware and malware detection system using modern techniques such as techniques of data mining approach to detect known and unknown malware samples

Jacobi Weighted Moduli of Smoothness for Approximation by Neural Networks Application

اعدت مقاييس النعومة للرياضيين الذين يشتغلون في نظرية التقريب والتحليل العددي والتحليل الحقيقي. ان قياس نعومة دالة باستمرارية اشتقاقها اكثر من مرة هي طريقة مجة جدا. ان الطريقة الافضل والاكثر ملائمة لقياس نعومة دالة هو استخدام مقياس النعومة. تم تعريف العديد من مقاييس النعومة وانواع من الدالي-K , من قبل الكثير من المشتغلين في نظرية التقريب. في هذا البحث تم اختيار اثنين من مقاييس النعومة وأحد انواع الدالي-K التي تم تعريفها مسبقا. بعدها قمنا ببرهان ان هذين المقياسين متكافئين تحت شروط معينة بالاضافة الى انهما يكافئان الدالي-K تحت نفس الشروط. وكتطبيق للعمل اعلاه قمنا بتقديم احد انواع مبرهنة جاكسون للتقريب باستخدام الشبكات العصبية.          Moduli of smoothness are intended for mathematicians working in approximation theory, numerical analysis and real analysis. Measuring the smoothness of a function by differentiability is two grade for many purposes in approximation theory. More subtle measurement are provided by moduli of smoothness. Many versions of moduli of smoothness and  K-functionals introduced by many authors. In this work we choose two of these moduli and prove that they are equivalent themselves once and with a version of K-functional twice, under certain conditions. As an application of our work we introduce a version of Jackson theorem for the approximation by neural networks

An unusual case of common carotid artery pseudoaneurysm caused by migration of swallowed sewing needle

Common carotid artery (CCA) pseuoaneurysms are most commonly a result of traumatic injuries. CCA pseudoaneurysm due to migration of ingested foreign body is an unusual occurrence. Here we report a case of a 50-year-old female who presented with a pulsatile swelling in the right lower neck for 2 months. Ultrasonography (USG) and Computed Tomography Angiography (CTA) of neck revealed a large partially thrombosed pseudoaneurysm involving the right common carotid artery. Sewing needle (metallic foreign body) was noted within the thrombosed portion of the pseudoaneurysm and was successfully removed at surgery followed by repair of the pseudoaneurysm.Keywords: Pseudoaneurysm; Metallic foreign body; CT angiography; PTFE graf

An intelligent routing approach for multimedia traffic transmission over SDN

Nowadays, multimedia applications such as video streaming services have become significantly popular, especially with the rapid growth of users, various devices, and the increased availability and diversity of these services over the internet. In this case, service providers and network administrators have difficulties ensuring end-user satisfaction because the traffic generated by such services is more exposed to multiple network quality of service impairments, including bandwidth, delay, jitter, and loss ratio. This paper proposes an intelligent-based multimedia traffic routing framework that exploits the integration of a reinforcement learning technique with software-defined networking to explore, learn and find potential routes for video streaming traffic. Simulation results through a realistic network and under various traffic loads demonstrate the proposed scheme's effectiveness in providing a better end-user viewing quality, higher throughput and lower video quality switches when compared to the existing techniques

Deep learning approach for real-time video streaming traffic classification

Video streaming services such as Amazon Prime Video, Netflix and YouTube, continue to be of enormous demands in everyday peoples’ lives. This enticed research in new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Video streaming services such as Amazon Prime Video, Netflix and YouTube, continue to be of enormous demands in everyday peoples’ lives. This enticed research in new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Then, data was pre-processed to select the desired features for video traffic classification. Based on the performance evaluation, the model produces an overall accuracy of 99.3% when classifying video streaming traffic using a multi-layer feedforward neural network. This paper also evaluates the DL approach’s effectiveness compared to the Gaussian Naive Bayes algorithm (GNB), one of the most well-known machine learning techniques used in Internet traffic classification. The model is promising to be applied in a real-time scenario as it showed its ability to predict new unseen data with 98.4% overall accuracy

Pengaruh Fraksi Penipisan (P) Air Tanah Tersedia Pada Berbagai Fase Tumbuh Terhadap Pertumbuhan, Hasil Dan Efisiensi Penggunaan Air Tanaman Kedelai (Glycine Max [L] Merr.)

Penelitian bertujuan untuk mengetahui pengaruh fraksi penipisan (p) air tanah tersedia pada berbagai fase tumbuh terhadap pertumbuhan dan efisiensi penggunaan air tanaman kedelai. Penelitian ini dilaksanakan di dalam rumah plastik, laboratorium lapang terpadu, Universitas Lampung pada bulan Oktober 2015 sampai dengan Januari 2016. Penelitian ini menggunakan rancangan Faktorial dalam Acak Lengkap (RAL) dengan 2 faktor perlakuan, yaitu faktor I (Fraksi penipisan air tanah tersedia, p) dan faktor II (fase tumbuh, F). Masing-masing perlakuan terdiri dari 3 taraf, yaitu faktor I terdiri dari P1(0,2), P2(0,4) dan P3(0,6) dari penipisan air tanah tersedia, dan faktor II terdiri dari fase vegetatif aktif (F1), fase pembungaan (F2), dan fase pembentukan polong (F3), dengan ulangan sebanyak 3 kali. Pengukuran evapotranspirasi tanaman acuan dilakukan pada fraksi penipisan 0,2 dari air tanah tersedia dengan menggunakan tanaman rumput. Hasil penelitian menunjukkan bahwa, perlakuan fraksi penipisan (p) air tanah tersedia pada berbagai fase tumbuhtidak berpengaruh terhadap pertumbuhan dan efisiensi penggunaan air tanaman kedelai.Tanaman kedelai pada perlakuan fraksi penipisan (p) air tanah tersedia tidak mengalami cekaman air pada semua perlakuan, karena tanaman sebelum mendekati batas bawah perlakuan segera diberi irigasi dan dikembalikan ke kondisi kapasitas lapang. Produksi tertinggi dengan nilai efisiensi penggunaan air tertinggi dicapai oleh perlakuan fraksi penipisan (0-0,2) air tanah tersedia pada perlakuan fase pembungaan (F2). Tanaman kedelai menghasilkan produksi yang tinggi pada fraksi penipisan 0,4 untuk perlakuan fase pertumbuhan aktif dan fraksi penipisan 0,2 untuk perlakuan fase pembungaan dan fase pengisian polong

Re-reading in Stylistics

Cognitive stylistics is primarily concerned with the cognitive processes – mental simulations – experienced by readers. Most cognitive stylisticians agree that experiences of reading texts are dynamic and flexible. Changes in the context of reading, our attentional focus on a given day, our extra background knowledge about the text, and so on, are all factors that contribute to our experience of a fictional world. A second reading of a text is a different experience to a first reading. As researchers begin to systematically distinguish between the ‘solitary’ and ‘social’ readings that constitute reading as a phenomenon (Peplow et al., 2016), the relationship between multiple readings and the nature of their processing become increasingly pertinent. In order to explore this relationship, firstly we examine the different ways in which re-reading has previously been discussed in stylistics, grounding our claims in an empirical analysis of articles published in key stylistics journals over the past two decades. Next, we draw on reader response data from an online questionnaire in order to assess the role of re-reading and the motivations that underpin it. Finally, we describe an exercise for the teaching of cognitive stylistics, specifically applying schema theory in literary linguistic analysis (Cook, 1994), which illustrates the need to distinguish between readings as part of an analysis. Through these three sections we argue that our experiences of texts should be considered diachronically, and propose that the different readings that make up an analysis of a text should be given greater attention in stylistic research and teaching

Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network

The employment of the brain signals electroencephalography (EEG) could supply a deep intuitive understanding for infants behaviour and their alertness level within the living environment. The study of human brain through a computer-based approach has increased significantly as it aiming at the understanding of infants’ mind and measure their attention towards the surrounding activities. The artificial neural network achieved a significant level of success in different fields such as pattern classification, decision making, prediction, and adaptive control by learning from a set of data and construct weight matrices to represent the learning patterns. This research study proposes an artificial neural network based approach to predict the rightward asymmetry or leftward asymmetry which reflects higher frontal functional connectivity in the frontal right and frontal left, respectively within infant’s brain. In the traditional methods, the value of asymmetry of the frontal (FA) functional connectivity is used to determine the rightward or the leftward asymmetry. While the proposed approach is trying to predict that without going through all the levels of the calculation complexity. The achieved work will supply a deep understanding into the deployment of the functional connectivity to provide information on the interactions between different brain regions

Germ Warfare in a Microbial Mat Community: CRISPRs Provide Insights into the Co-Evolution of Host and Viral Genomes

CRISPR arrays and associated cas genes are widespread in bacteria and archaea and confer acquired resistance to viruses. To examine viral immunity in the context of naturally evolving microbial populations we analyzed genomic data from two thermophilic Synechococcus isolates (Syn OS-A and Syn OS-B′) as well as a prokaryotic metagenome and viral metagenome derived from microbial mats in hotsprings at Yellowstone National Park. Two distinct CRISPR types, distinguished by the repeat sequence, are found in both the Syn OS-A and Syn OS-B′ genomes. The genome of Syn OS-A contains a third CRISPR type with a distinct repeat sequence, which is not found in Syn OS-B′, but appears to be shared with other microorganisms that inhabit the mat. The CRISPR repeats identified in the microbial metagenome are highly conserved, while the spacer sequences (hereafter referred to as “viritopes” to emphasize their critical role in viral immunity) were mostly unique and had no high identity matches when searched against GenBank. Searching the viritopes against the viral metagenome, however, yielded several matches with high similarity some of which were within a gene identified as a likely viral lysozyme/lysin protein. Analysis of viral metagenome sequences corresponding to this lysozyme/lysin protein revealed several mutations all of which translate into silent or conservative mutations which are unlikely to affect protein function, but may help the virus evade the host CRISPR resistance mechanism. These results demonstrate the varied challenges presented by a natural virus population, and support the notion that the CRISPR/viritope system must be able to adapt quickly to provide host immunity. The ability of metagenomics to track population-level variation in viritope sequences allows for a culture-independent method for evaluating the fast co-evolution of host and viral genomes and its consequence on the structuring of complex microbial communities