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Register a new userإدارة الخصوصية ضمن شبكات الحوسبة السحابية
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Syrian Virtual University رسالة ماجستير
Publication date
2018
fields
Informatics Engineering
and research's language is
العربية
Created by
Shamra Editor
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أصبح مفهوم الحوسبة السحابية من المفاهيم واسعة الانتشار والتي دخلت مختلف مجالات الحياة وقدمت فكرة مهمة هي نقل المعالجة والتخزين إلى مخدمات قابلة للمشاركة وبهذه الحالة يستطيع المستخدام أن يشغل تطبيقاته في اي مكان دون الخوف من فقدان البيانات أو من أيه مشكلة اخرى قد تطرأ على جهازه لان بياناته موجودة في مكان على الانترنت
No English abstract
References used
Peter Mell, Timothy Grance , The Nist Definition of Cloud Computing National institute of standarda and Technology 2011
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In this thesis an analytical study is done on existing cloud
resource allocation strategies and a comparative study summarize
them on the basis of technique used and objective as well as their
advantage and disadvantage.
نقوم أولا بالتحدث عن الحوسبة السحابية بصورة عامة إضافة الى المشاكل الأساسية التي تواجهها ونركز على المشاكل المتعلقة بالsecurity , ومن ثم نقوم بدراسة حالة الهجمات من النوع DOS وكيفية توظيف بعض تقنيات تنقيب المعطيات للكشف عنها والتعامل معها .
This study aimed to clarify the concept of cloud computing, their
characteristics and components, as well as the advantages and
disadvantages of the applications made available ways to take
ح .advantage of the Library environment
This study came
out with a set of the results which demonstrated
the importance of cloud computing to libraries by providing large
storage areas and expenditures, and the possibility to take
advantage of them do not require high skills, experiences.
problems relating of information security and privacy is a challenge
in dealing with them
Neural language models are known to have a high capacity for memorization of training samples. This may have serious privacy im- plications when training models on user content such as email correspondence. Differential privacy (DP), a popular choice
to train models with privacy guarantees, comes with significant costs in terms of utility degradation and disparate impact on subgroups of users. In this work, we introduce two privacy-preserving regularization methods for training language models that enable joint optimization of utility and privacy through (1) the use of a discriminator and (2) the inclusion of a novel triplet-loss term. We compare our methods with DP through extensive evaluation. We show the advantages of our regularizers with favorable utility-privacy trade-off, faster training with the ability to tap into existing optimization approaches, and ensuring uniform treatment of under-represented subgroups.
With the rapid growth of the size of the data stored in the cloud systems, the need for
effective data processing becomes critical and urgent. This research introduces a study of
the most important characteristics of databases management systems: H
ive, SQLMR, and
MariaDB Galera. Hive is a cloud database management system. SQLMR is a hybrid
system, which depends on the integration between the cloud and traditional systems
capabilities. While MariaDB Galera is a traditional database management system
developed to cope with the cloud characteristics. In this research, we show the most
important developments that have been on those systems, and then we compare their
performance in data processing based on the execution time of query operations with the
change of the volume of data. That is to identify the performance of those systems
practically and to know the developing requirements for access to optimized data
management system, and to help users in the selection of the database system that achieves
their requirements in terms of availability and scalability.
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