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الاداء الامثل لشبكات الاستشعار اللاسلكية باستخدام نماذج نشر مختلفة == An Optimal Performance of the Wireless Sensor Networks Using Various Deployment Models

Author name: عبد الناصر رياض فنجان سالم
Supervisor name: سعد طالب حسون الجبوري
General topic: Computer Science
Specific topic: Software
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: Wireless sensor networks (WSNs) today are widely used in various military and civilian applications and in the construction of a new concept called Internet of thinks (IoT), so it has been given great importance especially in recent years. In most WSNs applications sensors are deploying in random manner. Such randomness deployment produces trivial control on the network with no coverage guarantee and may achieve weakly connected network topology. Therefore, precise location can be often pursued for different nominated applications with the aim of configuring the topology of the network to reach to the requirements of preferred application. Most of the important WSN optimization techniques are to place the sensors in a deterministic manner to meet the required performance aims.In this dissertation several solutions are proposed to handle the deployment problem in WSN such as coverage, connectivity and reliability. Our suggestion depends on developing certain re - deployment approaches. These approaches are suggested and implemented in two virtual phases. In the first phase a random deployment was suggested then improves the locations of all the deployed sensors in the second phase. Once completing these phases a set of feasible locations will be available and can be used in the process of real sensor deployment.Seven algorithms are suggested, two of them were developed from the centralized optimization algorithms. The first is Particle Swarm Optimization (PSO), one of the common optimization methods. And the second is called Grid - distribution, where we considered this model to estimate the optimal number of sensors needed to cover a specific area. On the other hand, we have extracted two new models from Grid - distribution fundamentals, one of them to cover the border called barrier deployment, and the second is to cover center a certain area called center deployment.Three other optimization deployment algorithms are proposed to redeploy sensors after initial random deployment and improve coverage, connectivity and network reliability at the minimum cost. These algorithms are Distance based deployment, Markov based deployment and Angles based deployment. A mathematical model has been built for each of these proposed algorithms and has been implemented and tested by the Net Logo simulator. Each algorithm is executed in all sensors to achieve the desired objectives. The results of these algorithms were shown to be superior and dominate the results of existing algorithms such as Glowworm Swarm Optimization (GSO) and PSO_Voronoi.

اقتراح خوارزمية هجينة للتشفير الكتلي == Proposed Hybrid Block Cipher Algorithm

Author name: احسان احمد محمد لهمود
Supervisor name: عبد الكريم عكلة عبادي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: يعتبر التشفير من المجالات الجيدة في الوقت الحالي كما نعلم ان الامن شرط اساسي لاي عمل ومن اجل ذلك نحن بحاجة الى خوارزمية قوية جدا وغير قابلة للكسر لتوفير اجراءات امنية مشددة.لذلك نحن نحتاج الى خوارزمية للتشفير وفك التشفير لتوفير امنية عالية جدا وانتاجية جيدة جدا. اذا نظرنا الى العالم الحقيقي، هناك الكثير من المنظمات التي لديها قاعدة بيانات كبيرة جدا مع اجراءات امنية مشددة. وفقا للقلق الامني، تعمل بعض خوارزميات التشفير وفك التشفير لحماية المعلومات السرية مثل DES و3DES وAES وBlowfish.تم اقتراح وتصميم خوارزمية هجينة لتشفير كتلة او لفك تشفيرها مكونة من 256 بت باستخدام مفتاح بطول 288 بت. يتم تحويل كتله بطول 32 - حرف من النص الواضح او النص المشفر الى 256 بت. يتم جدولة المفتاح السري لكي يم تطبيقه في عملية التشفير وفك التشفير. يتم اخضاع كتلة النص الواضح الى عملية التقلب الاولية، وفي نهاية التشفير يتم اخضاع النص المشفر الى التقليب النهائي. تم تصميم الخوارزمية المقترحة للدمج بين اثنين من الخوارزميات (على اساس فيستيل وغير فيستيل).استخدمت في هذه الاطروحة بعض من معاير التشفير الكتلي مثل الانتاجية لتوليد كتلة مشفرة حيث حققت انتاجية الخوارزمية المقترحة قيمة 27.240 كيلوبت في الثانية. اما بالنسبة لهجمات القوة الغاشمة حيث تحتاج 1079 X 1.57سنة اذا تم تطبيقها لمهاجمة مفتاح الخوارزمية ، حققت الخوارزمية المقترحة نسبة اكثرمن ٥٠% ضمن معيار SAC حيث كانت النسبة (٥١.١٧%) وكذلك بالنسبة لمعيار BIC حيث حققت نسبة (٥٣.١٢%). تم تنفيذ الخوارزمية المقترحة باستخدام لغة البرمجة (Microsoft Visual Basic.Net 2008) وعلى حاسوب ذو مواصفات (Windows 10 pro, processor : Intel(R) core (TM) i7 - 3612QM CPU @ 2.10GHz, RAM 6.00 GB, and system type : 64 - bit operating system). | The Cryptography is very good area for research now a days. As we know that security is very primary requirement for the any business. And we need very strong and unbreakable algorithm which provides high security. We need encryption and decryption algorithm which is having very high security with very good throughput. If we look at the real world, lots of organizations are having very large database with high security. Some encryption and decryption algorithms are working behind confidential information like DES, 3DES, AES and Blowfish.A proposed hybrid algorithm designed to encrypt or decrypt block of a message that consisting of 256 - bit with control of a 288 - bit as a key length. The blocks constructed by converting a 32 - charecter block of plaintext or ciphertext into 256 - bit. The secret key is scheduled to be applied to encrypt and decrypt. Plaintext block will be subjected to an initial permutation IP, and final permutation. The proposed algorithm designed in a fashion which belongs on two algorithms (based on Feistel and Non - Feistel). In this dissertation, some components used like throughput of generate encryption block. It has achieved as 27.240 Kbps. Based on brute force attacks may be applied on this algorithm where it needs 1.57x1079 years to attack the applied key, the security is provided in this algorithm achieved results more than 50% within criteria of SAC is (51.17%) and BIC is (53.12%). The proposed algorithm were implemented using the programming language (Microsoft Visual Basic.Net 2008) within computer information of (Windows 10 pro, processor : Intel(R) core (TM) i7 - 3612QM CPU @ 2.10GHz, RAM 6.00 GB, and system type : 64 - bit operating system)

تقييم الية الثقة في شبكات المركبات == Evaluation of Trust Mechanism for VANETs

Author name: حوراء عادل نوري
Supervisor name: ستار بدر سدخان المالكي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: تدعم شبكة المركبات العديد من التطبيقات التجارية كانظمة النقل الذكية (ITS)، ولكن كان الدافع الاساسي وراء هذه الشبكات هو سلامة اتصالات الطريق الذي تعتمد فيه كل مركبة على الرسائل المرسلة لها من قبل نظائرها من المركبات الاخرى والتي قد تكون ضارة. ان الطبيعة المتغيرة والديناميكية لطبولوجيا الشبكة يجعل بامكان اي مركبة مغادرة الشبكة والانضمام اليها في اي وقت سواء كانت هذه المركبات موثوق بها ام لا. لذا يجب ان تتمكن كل مركبة من تقييم المعلومات الواردة لها من المركبات الاخرى واتخاذ القرارات بشانها والاستجابة لتلك المعلومات. عليه فبدون انشاء اليه مناسبة لادارة الثقة فان الاتصالات في هذه الشبكات قد تكون عرضه للتهديد الامني، حيث توجب الانظمة الامنية ان ياتي الارسال من مصدر موثوق لذا فان الثقة والامن مفهومان مترابطان لا يمكن عزلهما.لم يتحقق حتى الان تطوير نماذج امنة تماما لهذه الشبكات، لذا يهدف مجال البحث الجيد الى استثمار معظم الطرق السابقة في المؤلفات للبحث عن اطار عام لوضع اساس متين لتطوير الية احتساب السمعة والموثوقية في شبكات المركبات. يدعم هذا العمل امن شبكات المركبات من خلال استخدام تقنية الخوارزمية الجينية بالاضافة لنظرية اللعبة لتطوير الية ثقة متعددة الخصائص. | VANET support many commercial applications such as Intelligent Transportation Systems (ITS), but the original motivation behind it was safety of road communications where each vehicle has to rely on messages sent out by peer vehicles, which might be malicious. The dynamic changing nature of network topology makes any vehicle to leave and join the network at any point of time whether these vehicles were trusted or untrusted. Therefore, each vehicle must be able to assess, make decisions and respond to information received from other vehicles. So without having a proper mechanism for trust management, communication in VANET might be prone to security threat. Security systems impose that the transmission come from a trusted source, so trust and security are two interdependent concepts that there cannot be segregated.The development of fully secure schemes for these networks has not been entirely achieved till now. So, a good research field aims to exploit most of the previous approaches in literatures looking for a general framework to put solid basis to the development of Distributed Trust and Reputation Mechanism for VANET. The work supports the security of VANET by using a genetic algorithm technique in addition with game theory to develop a multi - featured trust mechanism

طريقة تحليلية لانظمة التشفير الصوتي البايومتري == Analytical Approach of Biometric Based Voice Encryption System

Author name: علي كاظم مطر
Supervisor name: ستار بدر سدخان المالكي | بهيجة خضر شكر
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: There is no absolute security for important systems can ever get because attackers have always the ability to broke and attack them through their disadvantages. These days, biometrics is used to raise protection rate compared with the traditional methods. Authentication systems and cryptosystems are some of the important aspects of the practical life that use biometrics. The biometric voice is one of these traits that can build suitable secure systems according to the varying in the biometric voice.In this dissertation, two proposed analyzers were introduced to analyze Authentication system of biometric voice and the encryption process of the cryptosystems. The Authentication analyzer was used Additive White Gaussian Noise (AWGN) to stimulate effect of background/ transmission channel noise, and analyze the behaviors of the authentication system using FAR and FRR biometric performance measures.Performing proposed Authentication analyzer found degradation in the accuracy about (9.6% to 19.2%) in Splashdata database, about (1.9% to 5.7%) in Texas Instrument of Massachusetts Institute and Technology (TIMIT) database, and 0% in Texas Instruments - Digits (TIDIGITS) database of all selected members cannot be rejected illegally even when AWGN was reached 20 dB. SNR. Also, performing proposed Authentication analyzer found that the highest security degradation was about 0.05769 in Splashdata database, 0.01923 in TIMIT database and 0.05769 in TIDIGITS database of all selected members even when AWGN was reached 20 dB. SNR.The second proposed analyzer (Encryption analyzer) was also tested on the same databases to analyze them according to three randomness tests from National Institute of Standards and Technology (NIST) packages (pre - encryption phase), then these databases were also tested using Cross - correlation and Chi tests (post - encryption phase). These two phases produced two results by implementing two Mamdani fuzzifiers to get the certainty of each result. The final output of proposed Encryption analyzer was produced by merging the two previous Mamdani fuzzifiers in another final Mamdani fuzzifier.The performance of the Encryption analyzer was proved by classifying good/bad Keystream using the (post - encryption tests) and also with the comparison of the average value of other different 5 randomness tests from NIST.Finally, the ANFIS structure was used to generalize the hidden relationships that trained from the three randomness tests (pre - encryption process). The generalization process made ANFIS having the ability to predict the values of unseen (untrained) patterns. ANFIS results were promising results according to the proposed Encryption analyzer.Chapter

استخدام تقنية الحساب المرن لتقييم RSA وAES == Soft Computing Technique to Evaluate RSA and AES

Author name: فرقد حامد عبد الرحیم
Supervisor name: ستار بدر سدخان المالكي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: Security evaluation algorithms can be considered as one of the most important challenges in computer networks. This is because of the growing data sharing among all clients (users). Therefore, the security level evaluation aspect of cryptography systems is recently appeared to be very important.In this work, evaluations of (RSA and AES) encryption methods are carried out by using Fuzzy Inference System (FIS) and Adaptive Neuro - Fuzzy Inference System (ANFIS). The editor of MATLAB (2013) is employed in this study and it contains a hybrid ANFIS facility between the Artificial Neural Network (ANN) and Fuzzy Logic techniques.First of all, designing and programming software codes for the first encryption method (RSA) have been simulated according to its original algorithm. Consequently, executing the RSA algorithm to collect the data values is implemented for the following parameters (message length, execution time, length of key and cipher message entropy). These parameters have been considered in the proposed approaches. So, the RSA data is used as the bases of the FIS inputs. Then, all the training and testing data values have been collected from the proposed FIS and prepared to be used in the next step (the ANFIS). The number of training samples has been selected to be 100 values by executing special software programs. These values have been utilized as follows : opening the ANFIS editor; loading the training data; determining the main ANFIS parameters and training the data with the least error tolerance. Subsequently, the number of testing samples has been chosen to be also 100 values by implementing special software programs. Hence, the evaluations are observed and the characteristics of the ANFIS which attained the best tested results have been benchmarked. Similar steps to evaluate the RSA by using large key numbers are implemented except of utilizing the parameter (key length) to study the influence of the key value on security evaluations. The proposed FISSecurity evaluation algorithms can be considered as one of the most important challenges in computer networks. This is because of the growing data sharing among all clients (users). Therefore, the security level evaluation aspect of cryptography systems is recently appeared to be very important.In this work, evaluations of (RSA and AES) encryption methods are carried out by using Fuzzy Inference System (FIS) and Adaptive Neuro - Fuzzy Inference System (ANFIS). The editor of MATLAB (2013) is employed in this study and it contains a hybrid ANFIS facility between the Artificial Neural Network (ANN) and Fuzzy Logic techniques.First of all, designing and programming software codes for the first encryption method (RSA) have been simulated according to its original algorithm. Consequently, executing the RSA algorithm to collect the data values is implemented for the following parameters (message length, execution time, length of key and cipher message entropy). These parameters have been considered in the proposed approaches. So, the RSA data is used as the bases of the FIS inputs. Then, all the training and testing data values have been collected from the proposed FIS and prepared to be used in the next step (the ANFIS). The number of training samples has been selected to be 100 values by executing special software programs. These values have been utilized as follows : opening the ANFIS editor; loading the training data; determining the main ANFIS parameters and training the data with the least error tolerance. Subsequently, the number of testing samples has been chosen to be also 100 values by implementing special software programs. Hence, the evaluations are observed and the characteristics of the ANFIS which attained the best tested results have been benchmarked. Similar steps to evaluate the RSA by using large key numbers are implemented except of utilizing the parameter (key length) to study the influence of the key value on security evaluations. The proposed FISSecurity evaluation algorithms can be considered as one of the most important challenges in computer networks. This is because of the growing data sharing among all clients (users). Therefore, the security level evaluation aspect of cryptography systems is recently appeared to be very important.In this work, evaluations of (RSA and AES) encryption methods are carried out by using Fuzzy Inference System (FIS) and Adaptive Neuro - Fuzzy Inference System (ANFIS). The editor of MATLAB (2013) is employed in this study and it contains a hybrid ANFIS facility between the Artificial Neural Network (ANN) and Fuzzy Logic techniques.First of all, designing and programming software codes for the first encryption method (RSA) have been simulated according to its original algorithm. Consequently, executing the RSA algorithm to collect the data values is implemented for the following parameters (message length, execution time, length of key and cipher message entropy). These parameters have been considered in the proposed approaches. So, the RSA data is used as the bases of the FIS inputs. Then, all the training and testing data values have been collected from the proposed FIS and prepared to be used in the next step (the ANFIS). The number of training samples has been selected to be 100 values by executing special software programs. These values have been utilized as follows : opening the ANFIS editor; loading the training data; determining the main ANFIS parameters and training the data with the least error tolerance. Subsequently, the number of testing samples has been chosen to be also 100 values by implementing special software programs. Hence, the evaluations are observed and the characteristics of the ANFIS which attained the best tested results have been benchmarked. Similar steps to evaluate the RSA by using large key numbers are implemented except of utilizing the parameter (key length) to study the influence of the key value on security evaluations. The proposed FISapproach confirmed that the RSA evaluation is successfully implemented to the ANFIS editor.All the previous steps are repeated for the AES encryption method except one difference. That is, the utilized parameters here are the (message length, execution time and cipher message entropy). Basically, two key values are determined for the AES, which equals to 128 bits. Likewise the RSA, the suggested procedures are applied to the AES and the proposed FIS approach confirmed that the AES evaluation is successfully implemented to the ANFIS editor.Finally, comparisons between this study and previous work, and between the RSA and AES are established. In addition, comparisons between the evaluated outcomes of the FIS and ANFIS have been investigated by using two statistical metrics.

عنقدة الصور اعتمادا على طريقة كسورية مطورة وتنقيب المخططات == Image Clustering Based on Developed Fractal Method and Graph Mining

Author name: فراس صبار مفتن
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: تشير عنقدة الصور الى تقسيم الصور الى عدة مجاميع. حيث كل مجموعة تسمى عنقود حيث يحتوي على صور متشابه في الخصائص ولكنها مختلفة عن الصور في العناقيد الاخرى. يمكن تفسر الخصائص الشاملة كميزات احصائية على انها خاصية للصورة تشمل جميع وحدات البكسل المستخدمة لحساب التشابه بين الصور. استخدمت هذه الاطروحة الكسور كخصائص محلية لتمثيل الصورة تستند الى مناطق بارزة في حين تبقى ثابتة لتغير نقطة النظر والاضاءة. تعتبر الكسور شائعه لقدرتها على استخراج ميزة التشابه الذاتي. ولفترة طويلة، استخدم الباحثون الكسور لضغط الصورة. على مدى السنوات الاخيرة، تم تطبيقها في التنقيب على البيانات. لهذه الاطروحة هدفين رئيسيين : اولا لدراسة القدرة على استخراج خصائص التشابه الذاتي من الصور دون استخدام بعد الكسور والذي يعتبر حساس للضوضاء العددية او التجريبية ومقيد بكمية البيانات. وثانيا لبناء الرسم البياني على اساس الميزات المستخرجة وتطور خوارزمية تجميع بالاعتماد على الرسم البياني.وينقسم النظام المقترح الى مرحلتين، بناء مصفوفة التشابه بواسطة طريقة كسورية وخوارزمية تنقيب المخططات. تم تطبيق PIFSلاستخراج ميزات التشابه الذاتي من صورة واحدة فقط. ولكن في هذه الدراسة كيفت PIFS لاستخراج ميزات التشابه الذاتي من العديد من الصور. بسبب ان PIFS تستغرق وقتا طويلا، فقد تم تكييفها للعمل مع تقنيات المطابقة والتقليل، وايضا تم استخدام الدالة الهاش للحد من تعقيد الوقت. واستخدم النظام المقترح مصفوفة تشابه لبناء المخطط ووضع خوارزمية عنقدة شبكية تعتمد على خصائص كسورية التوصيل بين العقد التي تمثل صور.استخدمت عدة بيانات لاختبار النظام المقترح. ولان النظام ينقسم الى مرحلتين، الاولى بناء مصفوفة التشابه والثانية هي خوارزمية تجميع الرسم البياني. لذلك، تم اختبار كل مرحلة بشكل منفصل. في الاول، يتم اختبار بناء مصفوفة التشابه (الميزات المستخرجة) مع خوارزمبة K - means لمعرفة صحة الميزات المستخرجة.وتم اقتراح طرائق لتقليل وقت التنفيذ ومقارنتها مع الطرائق التقليدية. وخفضت دالة الهاش التعقيد من O(m×n) الى O(m log⁡n) بينما قللت المطابقة والتقليل التعقيد الى O(m×n/t) حيث t عدد دوال المطابقة.اما طريقة التجميع البيانية المقترحة تم اختبار صحتها باستخدام البيانات الحقيقية واستخدمت المقاييس النمطية، الموصلية، التغطية، وكثافة الجودة وتم عرض النتائج والتحقق من صحتها من الناحية العددية والبصرية مع عدد عقد المختلفة. وقد اظهرت النتائج التي تم الحصول عليها دقة بين 0.80 و0.99 لجميع المقاييس.واظهرت النتائج ان للكسور قدرة كبيرة على استخراج ميزة التشابه الذاتي لاستخدامها في التنقيب عن الصور مثل التجميع. واعطت خصائص التشابه الذاتي كسورية نتائج جيدة. وان الميزات المستخرجة مشابه الى مصفوفة المجاورة التي يتم استخدامها لتمثيل الرسم البياني. لذلك، تعتبر بنية جيدة لتمثيل الرسم البياني. | Image clustering refers to the division of images into various sets of images. In this regard, each set known as cluster includes images that are similar in features to each other but different those of other sets. The global features as statistical features can be interpreted as a particular property of image involving all pixels were used to calculating similarity among images by most of the researchers. This thesis used fractal features as local features to represent an image based on salient regions while remaining invariant to viewpoint and illumination changes. Fractal is popular because of their ability to extract the self - similarity feature. For a long time, researchers used fractals for image compression. Over the latest years, they have been applied in mining. This thesis has two major purposes, first to studies the ability to extract fractal Self - similarity features from images without using fractal dimension which is sensitive to numerical or empirical noise and limitations in the amount of data. Second to constructs graph based on extracted features and develops graph cluster algorithm.The proposed system is divided into two phases, the Similarity Matrix construction by a fractal method and a Graph Clustering algorithm. Partitioned Iterated Function Systems (PIFS) is applied to extracting Self - similarity features from just one image. This study developed PIFS to extracting Self - similarity features from many of images. Since the PIFS algorithm is time - consuming, it has been adapted to work with Map - Reduce techniques and also hash function was used to reduce the time complexity. The proposed system used similarity matrix to construct a graph structure and developed a graph clustering algorithm based on connectivity fractal features among nodes that represents as images.Each phase was tested Separately. In the first phase, Similarity Matrix construction (features extraction) is tested with K - means clustering algorithm to find out the correct features extracted. The B - Cubed recall and precision are estimated with good results to precision and recall accuracy.Then proposed methods of reducing time complexity results is presented and compared with traditional methods. The hash function reduced the complexity O(m×n) to O(m log⁡n) while Map/reduce technique reduce the complexity O(m×n) to O(m×n/t) for time where t is a number a of map task.The second phase, Graph Clustering algorithm is tested with the real - world graph dataset. The clustering result was evaluated by Modularity, Conductance, Coverage, and Density Quality Metrics and the results were presented and validated both numerically and visually with different nodes number. The obtained results have shown accuracy between 0.80 and 0.99 for all metrics.

نظام الكشف التعاوني عن هجومات الفيضان الموزعة للحرمان من الخدمة والتعقب المستوحى من مجتمع العناكب الاجتماعية == Collaborative Detection System of DDoS Flooding Attacks and Tracing Inspired by Social Spiders Society

Author name: عادل محمد سلمان القريشي
Supervisor name: صفاء عبيس المعموري
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: لا تزال شبكة الانترنيت تعاني من المشاكل الامنية التي تهم بشكل رئيسي الاشخاص الذين يستخدمون اجهزتهم للاتصال بالانترنت، سواء كانوا افراد او مؤسسات كبيرة. الهجمات الموزعة للحرمان من الخدمة، لا تزال واحدة من اهم المواضيع التي يتم مناقشتها حاليا في تهديدات امن الشبكات للشركات التي تقدم الخدمات لعملائها. في هذه الاطروحة، تم اقتراح نظام الكشف التعاوني. واستند على مرحلتين : (1) مرحلة الكشف؛ (2) مرحلة التعقب. اعتمادا على الفكرة المستوحاة من مجتمع العناكب الاجتماعية، تم تصنيف اجهزة التوجيه الى نوعين، على النحو التالي : (1) جهاز التوجيه الذكر، الذي هو مرتبط مباشرة مع الخادم؛ (2) جهاز التوجيه الانثى، والذي هو كل جهاز توجيه غير مرتبط مباشرة مع الخادم. ويتميز النظام المقترح بانه حل قائم على جهاز التوجيه وعلى فحص التدفقات.يمكن تقسيم مرحلة الكشف الى اربع خطوات، على النحو التالي : (1) جمع البيانات؛ (2) معالجة البيانات واستخراج الميزات؛ (3) بناء نموذج التصنيف، باستخدام خوارزمية شجرة القرار عالية السرعة (VFDT) كخطوة للكشف المبكر، والتي سيتم استخدامها من قبل كل جهاز توجيه انثى في الشبكة؛ (4) كشف الشذوذ (الهجوم) باستخدام خوارزمية الغابات العشوائية (RF) للتصنيف، والتي سيتم تنفيذها في كل جهاز توجيه ذكر. الجمع بين هاتين الخوارزميتين سوف ينتج عنه خوارزمية تصنيف جديدة تسمى هوفدينغ الغابات العشوائية (HRF).تبدا مرحلة تتبع مصادر الهجوم عندما يتم العثور على بيانات الهجوم. جهاز التوجيه الذكر القريب من الخادم الضحية سوف يتتبع مصادر الهجوم بالاعتماد على قيمة الاهتزاز للتدفق، ثم رفع الانذار وارسال جميع المعلومات الى مسؤول الشبكة لاتخاذ الاجراءات اللازمة. وقد استلهمت قيمة الاهتزاز من مجتمع العناكب الاجتماعية، والذي هو قيمة تاثير جهاز التوجيه الانثى على كل تدفق يمر من خلاله.وقد تم استخدام برنامج محاكاة شبكة NS3 لتوليد بيانات الشبكة. ثم الحصول على النتائج واختبار النظام بواسطة برنامج مبرمج باستخدام لغة C++. وعلاوة على ذلك، طبقت عدة تجارب، وتم اعتماد تجربتين لاختبار النظام المقترح، الاول هو 90 ثانية، في حين ان الثانية هي 1200 ثانية. اجريت هذه التجارب لتوليد البيانات العادية وكذلك توليد بيانات هجوم الفيضان الموزع للحرمان من الخدمة للنوعين TCP وUDP. تم اختبار البيانات التي تم توليدها لاثبات ما اذا كانت مشابهة للبيانات الحقيقية عن طريق اختبار اثنين من الخصائص التي هي التباين العالي والتشابه الذاتي. وقد اظهرت النتائج ان البيانات التي تم توليدها لها نفس خصائص البيانات الحقيقية، وتمت الموافقة على نسبة حوالي 95٪.بالاضافة الى ذلك، لتقييم اداء خوارزمية هرف الجديدة، تم استخدام ثلاثة تدابير : (1) نسبة دقة التصنيف، والتي كانت 99.9983٪ و99.9990٪ على التوالي لكل من التجارب (90 ثانية و1200 ثانية). (2) معدل الكشف، والتي تبين 9.9996٪ و99.9997٪، على التوالي، لكلا التجربتين. و(3) نسبة الانذار كاذب، كان 0.016٪ و0.0088٪ على التوالي لكلا التجربتين. وكان متوسط وقت الكشف 21.71 و28.46 ثانية لكل من التجارب على التوالي.يستخدم النظام المقترح مبدا تقليل السمات المستخدمة في التصنيف، مما ادى الى انخفاض في حجم الذاكرة المستخدمة بنسبة 62.96٪ وانخفاض في مساحة القرص الثابت المستخدم بنسبة 51.75٪.واخيرا، في عملية البحث عن المفقودين، والوصول الى اقرب جهاز التوجيه الاناث الى مصدر الهجوم، حيث تم تحديد معظم هذه الموجهات، لكلا التجربتين، مع نسبة 100٪. | The Internet still suffers from security problems which are the main concern for those connected via their devices, whether they are individuals or institutions. The Distributed Denial of Service (DDoS) attacks are still one of the most significant current discussions regarding network security threats for companies providing services to their clients.In this dissertation, a collaborative detection system which proposed is based on two parts : (1) the Detection phase, and (2) the Tracing phase. Inspired by the social spider’s society, the routers were classified into two types : (1) Male router, which is near the server and directly connected with it; and (2) Female router, which is near the user and directly connected with it or between the user and the server. The proposed system is characterized as a router - based and flow - based solution.The detection phase can be divided into four steps : (1) data collection; (2) data preprocessing and extraction of features; (3) building the classification model, using a Very Fast Decision Tree (VFDT) algorithm as an early detection step, which will be used by each female router in the network; and (4) anomaly (attack) detection using the Random Forest (RF) algorithm for classification, which will be implemented in each male router. The combination of these two algorithms will generate a new classification algorithm called the Hoeffding Random Forest (HRF).The tracing phase will be started when the attack data is found. The male router near the victim server will trace the attack sources based on the value of the vibration of the flow, then raise the alarm and send all the information to the network administrator, to take an action. The vibration value has been inspired by the social spider’s society, which is the effect of the female router on each flow passing through it.NS3 network simulation software has been used to generate the network data. Then obtain the results and test the system by a software programmed by C++. Moreover, several experiments were applied, and two experiments were adopted to test the proposed system; the first is 90 seconds, while the second is 1200 seconds. These experiments were performed to generate normal data and DDoS flooding attack data for TCP and UDP types. The generated data has been tested to prove if it is similar to the real data by testing two critical characteristics : high - variability and self - similarity. The results show that the generated data has the same characteristics as the real data, and is approved with ratio approximately 95%.Additionally, to evaluate the performance of the new HRF algorithm, three measures have been used : (1) classification accuracy ratio, which was 99.9983% and 99.9990% respectively for both experiments (90 sec. and 1200 sec.); (2) detection rate, showing 9.9996% and 99.9997%, respectively, for both experiments; and (3) false alarm, was 0.016% and 0.0088% respectively for both experiments. The average of the detection time was 21.71 and 28.46 seconds for both experiments respectively.The proposed system uses the principle of reducing the features that used in the classification, which led to a reduction in the used memory size by 62.96% and a reduction in the used hard disk space by 51.75%.Finally, in the tracing process, accessing the nearest female router to the source of the attack, where most of these routers have been identified, for both experiments, with ratio 100%.

تنقيب محتويات وبيانات استخدام الشبكة العنكبوتية بالاعتماد على تقنيات العنقدة المحدثة == Web Content and Usage Mining Based on Modified Clustering Techniques

Author name: احمد جبار عبيد
Supervisor name: توفيق عبد الخالق الاسدي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: The extensibility of diversified information that available on the Web along with massive users' have accessed to the Web services frequently produce several challenges related to such critical tasks such as controlling, monitoring and perception of the Web contents. However, novel techniques must be used to satisfy the modernistic requirements and provides better understanding to the colossal collection of diversity data types that is growing in fast manner every day on the Web.Web Mining is an extension of Data Mining techniques upon the data that stored on the Web. Web Mining is classified into three categories based on the type of data that used in mining process which are : Web Content Mining (WCM) is concern with the process of extract useful information from Web pages' contents, Web Usage Mining (WUM) is concern with discovering users' access pattern from Web usage data, and finally Web Structure Mining (WSM) is concern with extracting knowledge from the structure of the hyperlinks. Web documents are the most complex data that scattered on the Web in random way and a lot of these documents are created without any prior information. Unsupervised Data Mining Clustering technique, is one of the most usage techniques that aim to portioned out the objects into set of coherence groups, where the objects in a cluster are having common patterns than objects in other clusters.In this dissertation, the task of Web Mining is divided into two parts based on the data collected from the universities of (Kufa, Technology, Anbar and Diyala). First part is hold the Web documents by applying WCM techniques upon the Web Pages and Images of the universities Web sites, while second part is consider applying WUM techniques upon the Web usage data that collected from the Kufa university Web server. Proposed system consist of two parts : first part uses a novel approach to pre - process and extract unobserved patterns from Web pages' text blocks content,

تمييز حركة الكائن المفرد اعتمادا على نظرية تاكوشي للامثلية ومجموعة الخام للتصنيف == Single Object Motion Categorization Based on Taguchi Method Optimization and Rough Set Classification

Author name: عادل عباس مجيد الربيعي
Supervisor name: اسراء هادي علي الشمري
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: تعتبر انظمة التتبع الفيديوية ذات اهمية كبيرة في عالمنا الحديث. لاعتبارها احد الفروع الهامة من علوم الحاسوب التي تتعامل مع عدة مواضيع مثل الامن، الطبية، القضائية او الطب الشرعي، الرياضة وغيرها من المجالات الحيوية والحياتية الاخرى.ان المشكلة الاساسية التي تم تناولها ودراستها في بحثنا هذا كيفية الكشف عن حركة الاجسام او الاشخاص والتركيز لايجاد نوع وشكل الحركة للاجسام في الافلام.الحصول على معلومات اضافية من الفيديو ادت الى تجميع بعض الافكار لبرهنة او دحض بعض الحقائق. وكذلك ايجاد الدوال المناسبة لها والتي تمثل نوع الحركة للجسم، حيث تم استخلاص الصفات المهمة لمسار الجسم مع تحديد وزن كل صفة وهذا مما يؤدي تقليل الزمن المستهلك في تطبيقات التعقب الفديوي. تم استخدام طرق الرياضيات الحديثة لغرض تصنيف الحركات المتنوعة والمتشابهة في الشكل للاجسام التي يتم تعقبها بالاعتماد على قاعدة بيانات ذات مقاييس عالمية. هناك الكثير من التحديات التي تواجه عملية تعقب الاهداف المتحركة، مثل فصل الجسم او الهدف عن خلفية المشهد، نحن نستخدم طريقة محدثة من الرسم البياني التراكمي لبناء قالب للمشهد الخلفي. بعد ايجاد مسار الجسم نحن نختار عدد من الصفات الملائمة مثل (الازاحة، السرعة، الفرق في الطول، الميل) لغرض تحديد شكل وطبيعة حركة الجسم.في بحثتا هذا استخدمنا ثلاث طرق وقارنا بينها (الميل، الانحدار، وصف فورير) لحركة الاجسام لكي نحدد شكل الحركة (مستقيم، دائرة، قوس، بيضوي، متذبذب، حرف اس ....الخ) واستنتجنا ان طريقة الميل هي الافضل من حيث الزمن المستهلك وغير مكلفة حسابيا. في مرحلة الامثلية التي تعتبر جزء مهم في انظمة التعقب الفيديوي، وظفنا نظرية تاكوشي لتحديد الاعلى وزنا لافضل خاصية من الخواص المستخلصة مما يؤدي لتقليل الزمن المستهلك في التطبيقات. لتصنيف انواع عديدة من حركة الاشخاص نحن نعتمد على موديل مجموعة الخام لبناء نظام المعلومات وعدد من القواعد لتمييز شكل الحركات المتداخلة مثل (الانحناء، رفع اليد والساق في نفس المكان، القفز مع الحركة، القفز في نفس المكان، الركض، الحركة الجانبية، القفز بقدم واحدة، المشي، الحركة الموجية) في عملية التصنيف. في النهاية، للكشف عن البحث وما يتضمنه من تجارب يمكن متابعة الفصل الثاني والثالث بشكل مفصل علما ان وثوقية النظام بلغت بحدود 93% بعد اجراء الكثير من التجارب بالاعتماد على قاعدة بيانات قياسية تسمى "ويزمان | Video tracking systems (VTS) is a matter of interest in this modern world, because it regarded as one of important branches of computer science which deals with several subjects such as security, medical, judicial or forensic, sports and other vital fields of life.The main problem that has been addressed, studied and analyzed in this thesis is how can detect and recognize objects (persons) motions? farther more this work was concentrated on finding the shape and form of a movement of person or objects in a video. Getting additional information from a video will enable the author to sum the ideas in order to prove or disprove some facts. For instance, finding and manipulating the trajectory of object and mathematical models used in analyzing. Finding the suitable functions which represent types of objects’ motions, extract important features of trajectory object’s moving, in order to find optima features by determine the weight of each features. This reduce the consume time in video tracking application. Using the modern mathematical models to classify object motion and determine the types and form of them. This is based on standard database (Weizmann). There are some difficulties facing the process of tracking moving targets such as separate the object or target from the background of scene. In order to build a background template model which is used an upgrade accumulative histogram technique.Finding the trajectory of object, and selecting a number of appropriate motion attributes such as (displacement, velocity, differences in length and slope), enable us to determine the form and the nature of the motion object movement.In this work three methods “Slope, Regression and Fourier descriptors” have been studied, and a comparison among them was made, and determines the shape of the movement (straight line, circle, arc, ellipse, oscillating, S - shaped…etc.) was detected. It was found, that the slope method was the best in terms of consumed time or computationally inexpensive.The optimization stage regards a core part of a video tracking, specified Taguchi method have been used in this work in order to assign in high value of weight for best features extraction and it has reduced the consumption of analysis time.The classification of persons motion depends on rough set model to implement information system and number of rules in distinguishing forms of overlapping movements types such as to (bend, jack, jump, pjump, run , side, skip, walk and wave). In the end, the detection of this work implicitly tested in chapter two and chapter three. Thesis reliability up to 93% after a lot of testing based on the standards database is called “Weizmann”.

خوارزهية التوجيه الهجينة لاتصاللات الماكنة مع ملكنة == Hybriid Routiing Allgoriithm for Machiine to Machiine Communiicatiion

Author name: باسم جميل علي
Supervisor name: سعد طالب حسون الجبوري
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: The wireless communication devices have witnessed rapid growth in the recent years. Such growth and its useful applications led to the appearance of new applications known as "machine - to - machine" (M2M) communications. M2M plays a big role in finding the best hopeful explanation to change the current and the future smart widespread requests. Most of the smart wireless devices may perform as servers, collection of data and/or delivering the data at real time to users in a certain collaborative fashion.M2M communication domain consists of a huge number of tiny nodes and gateway (or sink) that are suffer from suffer from resource constrains like power limitation, storage capacity, radio limitation, data processing, etc.. Thus, it is necessary to find methods to increase node's lifetime as long as possible and consequently the overall sensor network. M2M devices consume considerable amount of energy due to communication process comparing to other process. This process depends on message size and the distance between the sender and the recipient. Thus reducing the packet size and finding a low energy aware routing procedure is necessary to save nodes energy.This thesis adopted compressed sensing (CS) as a modern data compression technique, modified Gossip algorithm as a flat protocol and introduced hybrid Gossip based low energy adaptive clustering hierarchy (LEACH) protocols as a new hybrid routing algorithm. CS combined with LEACH protocol named LEACHCS and the results that are reported from LEACHCS showed that the communication process can be improved in term of the channel bandwidth (B.W) utilization, increasing network throughput and saving node's communication energy.Gossip data aggregation technique is a biologically inspired paradigm of contagion inspired from behavior of the disease infection process. Its procedure is based on the help of neighboring nodes and employs the randomization technique to form a chain of the intermediary nodes (route). The modification of Gossip based on the selection operation of the next node hop. This thesis introduced three versions of modifying Gossip : a) Modify Gossip named (DGossip), in which a chain of intermediary nodes can be formed according to the relative node's energy and relative nodes displacement to the sink instance of randomization technique in the original Gossip. b) The formation of intermediary nodes based on the relative energy of neighbor nodes and nearest node to the source node called EN_Gossip. c) A hybrid of EN_Gossip and EL_Gossip named ENL_Gossip is introduced as a new version. In ENL_Gossip, a chain of intermediary nodes is collected through alternating use of both EN_Gossip first then EL_Gossip starting from the source node till reached the sink.The results showed that the DGossip is significantly better than others in term of the average remaining energy of network and latency time (in terms of number of hops), while ENL_gossip outperforms the others in term of network's live time.A new hybrid algorithm is proposed which combined Gossip as a bio - inspired technique with LEACH as a hierarchical multi - hop routing algorithm called LEACHGossip algorithm. This algorithm uses LEACH for clustering configuration purpose, while Gossip applies for each CH (or normal node) that is away (do m) from the sink (or from its associated CH). The simulation results proved that it outperforms LEACH about more times in terms of congestion between CHs and BS, node still alive and energy saving. Thus, the above mentioned procedures can be considered as efficient communication protocols for M2M communication networks in term of energy saving.

تحديد مكان وهوية المتكلم باستخدام تقنية توجيه حزم الاشارة المحسنة

Author name: علي يعكوب يوسف
Supervisor name: حسين عطية لفتة الخالدي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: Automatic speech recognition (ASR) systems perform well when using a close - talking microphone, However, many environments (Hands - free) where the use of such microphones is undesirable for reasons of convenience. In a hands - free environment, the noise and reverberation degrade the accuracy of recognition. An enhanced approach using microphone array for speaker localization and enhancement of speech signal input to an automatic speech identification system was proposed. The proposed system using enhanced beamforming technique based on Minimum Variance Distortionless Response (MVDR) for speaker localization with multi - microphone arrays. The strongest output beam signal corresponding to selected microphone array, used for the speaker identification. The identification phase based on using Mel Frequency Cepstrum Coefficient MFCC for feature extraction and enhance LBG algorithm for speaker modeling.Speaker identification accuracy in using proposed method were compared with conventional beamforming method, It was found that the higher recognition accuracy than previous approaches, and in experiments using speech signals that were artificially corrupted by additive noise. The proposed system provided a consistent, improvement in recognition accuracy for several experiments in simulation environments. It is also showing the benefit of usingmicrophone array processing. The localization phase evaluated using SNR, showing enhanced ratio after applying enhanced beamforming that estimate speaker location. The results showing localization accuracy 96.8% and 98.1% recognition accuracy where achieved.

نظام توصيات قائم على الويب لانتشار الاوبئة == Web - Based Recommender System for Spread Epidemics

Author name: حيدر محمد حبيب مجيد
Supervisor name: نبيل هاشم الاعرجي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: The usage of Online Social Networks, such as Facebook and Twitterbecomes more and more popular in order to exchange and disseminate news andinformation in real - time. Twitter in particular allows the instant dissemination ofshort messages in the form of microblogs to followers. This dissertation exploresand examine the usage of how social networks, such as the microblogging toolTwitter, can help in the detection of spreading epidemics and reducing time delaybetween the emergence of disease and report sick to the health authorities suchas World Health Organization (WHO).Text classification has been used to classify the patients and non - patients(positive / negative). Sentiment Analysis (SA) and Linear Support VectorClassifier (LSVC) have been applied in the classification patients. In thisdissertation, four diseases have examined. Diseases that have most similarity intheir symptoms have been taken in order to classify patients based on theirsymptoms by applying a recommendation system techniques. Symptoms - basedHealthcare Recommender System is new approach in this work. It uses patientsymptominstead of user - item in traditional Collaborative Recommender System.Collaborative Filtering (CF) has been applied in order to recommend whichdisease the patient may has. CF shows an indicator that users on Social Networkshave not enough knowledge to mention all symptoms for specific disease, that’sled to classify patients to more than one disease according to common symptomsthat mentioned by patients.Geolocation of users that classified as patients has been extracted in orderto recommend health authorities that there is a certain area might has a beginningof spread disease. An implicit geocoding of users has been extracted by usingGoogle Maps Geocoding API to avoid neglecting those who don’t have explicitgeolocation.IISuspected areas has been weighted by computing a Confidence Factor(cFactor) of Tweet source whatever it comes from mobile or desktop. cFactorhelp in reducing time consuming into 29% of collecting and processing data.Weighted and Geographic Symptoms - based Recommender (WGSR) model hasbeen created detect, classify and visualize patients on the map.The accuracy of WGSR model reached to %94 in the classification andmore than %80 with the real reports of World Health Organization (WHO) whichrefers as a very good and can be improved for better results.

تعديل قواعد الارتباط الموزعة لتحليل الجرائم == Modification Distributed Association Rules For Crimes Analysis

Author name: ايناس محمد حسين سعيد
Supervisor name: عماد كاظم جبار الفتلي | سـكينه حسن هاشم
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Baghdad
First pages:
Abstract: الجريمة منحت الاولوية القصوى من قبل جميع الحكومات لما لها تاثير كبير على المجتمع.ان تحليل الجرائم المعقدة تتطلب الذكاء البشري والخبرة. لقد باتت وكالات تطبيق القانون مثل الشرطة تواجه مشكلة الحجم الكبير للبيانات التي يجب معالجتها وتحويلها الى معلومات مفيدة | Crime is a major issue what has been given the top priority by all governments. Law enforcement agencies like that of police today are faced with large volume of data that must be processed and transformed into useful information. Accordingly to, solving

اكتشاف العيب للصور الشعاعية مع التعليق باستخدام المربع الاصغر لماكنة الدعم الموجه وقواعد عامة وخاصة للتصنيف == Defect Detection of Radiography Image With Annotation Using Lssvm_Gsc Techniques

Author name: وفاء محمد سعيد الاسدي
Supervisor name: يحيى مهدي هادي الميالي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
Key words:
  • Image Processing
  • Weld Image Defect Detection
  • Image annotation
  • Radiography Image
First pages:
Abstract: استرشادا بالشعوربالمسؤولية ورغبة في مساعدة اكتساب معرفة عميقة حول دراسة تنوع العيوب في صور التصوير الشعاعي، لهذا سنتعرف على هذه العيوب الموجودة في هذه الصور، ومن ثم اعطاء كل صورة بعض الكلمات التي تعكس محتوياتها الرئيسية، وبناء قاعدة بيانات للصور مع الشرح | Guided by the sense of responsibility and its desire to help gain a deep knowledge and the diversity of the defects exist in the radiography images, this Dissertation recognizes the defects exist in the these images, then given each image some keywords re

تصميم وبناء نظام هجين للتنبؤ بالشكل الثلاثي للبروتينات == Design And Implementation of Hybrid System For Protein Tertiary Structure Prediction

Author name: مهند محمد جاسم الياسري
Supervisor name: نبیل ھاشم الاعرجي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:
Abstract: تبقى مشكلة التنبؤ ببنية البروتين كنوع من التحدي العقلي والتنفيذي على حد سواء. (PSP) تبقى مشكلة التنبؤ ببنية البروتين وبالتالي فان اهداف هذه الاطروحة هي : اولا، اقترح منظورا جديدا للمساهمة في تطوير وزيادة المعرفة في مجال "طي البروتين العملية" (عن طريق وصف | The Protein Structure Prediction (PSP) problem remains as both mental and implemental challenge. Therefore, the objectives of this dissertation are : First, suggest new perspective for contributing in development and knowledge increasing in the "protein f

نظام ذكي لاكتشاف وتمييز الانسان == Intelligent Human Detection And Recognition System

Author name: نهى جميل ابراهيم
Supervisor name: احمد طارق صادق العبيدي | عماد كاظم جبار
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Baghdad
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Abstract: نظام مراقبة الفيديوي خصوصا للبشر والعربات ھو احد مواضيع البحث الصعبة الحالية في مجال الحاسوب. الكمية الھائلة للبيانات تجعل عملية المراقبة غير قابلة للتطبيق لضمان مراقبة متيقظة من قبلالمشغلين للفترات الطويلة من الوقت بسبب الرتابة والاعياء. كنتيجة، تس | Video surveillance system especially for humans and vehicles, is one of the current challenging research topics in computer vision. The massive amount of data involved makes it infeasible to guarantee vigilant monitoring by human operators for long period

تطوير التخويل المعتمد على البايومترك لنقل بيانات امنة عبر البيئة السحابية == Developing A Biometric Based Authentication To Secure Transferring Data Via Cloud Environment

Author name: احمد عبد الرضا عباس
Supervisor name: وسام سمير بهية
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:

تقليل الاشعارات الخاطئة عند الكشف عن البرمجيات الخبيثة باستخدام تسلسل ايعازات API == Reducing False Notifications In Malware Detection Using API Calls Sequence

Author name: حسين لفتة حسين
Supervisor name: عباس محسن البكري
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:

طريقة هجينه لاكتشاف وتعقب الكائنات المتحركة في ملف فيديو == A Hybrid Approach for Detection and Tracking of Moving Objects in Video File

Author name: جلال حميد عواد
Supervisor name: عامر صديق الملاح
General topic: Computer Science
Specific topic: Video Processing
Degree: Doctorate
Language: English
University location: Babylon
First pages:

اطار عمل للاستشارة التعاونية والتشخيص عن بعد بالاعتماد على الحوسبة السحابية == on cloud telecollaboration consultation and diagnosis framework based on agent

Author name: امير كاظم هادي
Supervisor name: عباس محسن البكري
General topic: Computer Science
Specific topic: Computer Networking
Degree: Doctorate
Language: English
University location: Babylon
First pages:

تنفيذ نموذج امني باستخدام التشفير المعتمد على الـ DNA == Implementation of secure model using DNA-based cryptography

Author name: ياسين حكمت اسماعيل
Supervisor name: نجلاء بديع ابراهيم الدباغ
General topic: Computer Science
Specific topic: Data Security
Degree: Doctorate
Language: Arabic
University location: Mosul
First pages:

التنفيذ والتحقق من اطار عمل لخادم افتراضي باستخدام هايبر في == Implementation and Investigation of Server Virtualization framework Using Hyper-V

Author name: رضوان يونس امين يونس
Supervisor name: اسماء ياسين حمو
General topic: Computer Science
Specific topic: Computer Architecture
Degree: Doctorate
Language: English
University location: Mosul
First pages:

كشف الاعلانات الغير المرغوب بها والملصقة على صفحات الويب باستخدام خوارزميات تعدين البيانات == Spam Detection on the Web Sites Pages Using Data Mining Algorithms

Author name: ان زكي ابلحد
Supervisor name: بسام علي مصطفى
General topic: Computer Science
Specific topic: Network Security
Degree: Doctorate
Language: English
University location: Mosul
First pages:

تقنية جديدة لصهر الصفات لنظام استرجاع الصور باستخدام واصفات اللون الملمس والشكل == A New Features Fusion Technique for Image Retrieval System Using Colour, Texture, and Shape Descriptors

Author name: فاتن عباس مهدي
Supervisor name: عبد الكريم عكلة العبادي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Babylon
First pages:

توليد انظمة خبيرة باستخدام وكيل المعرفة == Expert Systems Development Using Knowledge Agent (ESDKA)

Author name: عباس محسن البكري
Supervisor name: هلال محمد يوسف | هلال هادي
General topic: Computer Science
Specific topic: Computer Science
Degree: Doctorate
Language: English
University location: Baghdad
First pages:
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