دانلود رایگان مقاله سیر تکاملی سیستم کلان داده از دیدگاه کاربرد امنیت اطلاعات

عنوان فارسی
سیر تکاملی سیستم های کلان داده: از دیدگاه کاربردهای امنیت اطلاعات
عنوان انگلیسی
The Evolvement of Big Data Systems: From the Perspective of an Information Security Application
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
9
سال انتشار
2015
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E417
رشته های مرتبط با این مقاله
مهندسی کامپیوتر و مهندسی فناوری اطلاعات
گرایش های مرتبط با این مقاله
مهندسی نرم افزار، برنامه نویسی کامپیوتر، امنیت اطلاعات و رایانش امن
مجله
تحقیقات کلان داده - Big Data Research
دانشگاه
کالج علوم کامپیوتر، دانشگاه ژجیانگ، هانگزو، چین
کلمات کلیدی
نگاشت کاهش، Pregel، جرقه، تجزیه و تحلیل بلادرنگ، امنیت اطلاعات
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

Abstract


Recently, Google revealed that it has replaced the 10-year old MapReduce with its new systems (e.g., DataFlow) which can provide better performances and support more sophisticated applications. Simultaneously, other new systems, such as Spark, Impala and epiC, are also being developed to handle new requirements for big data processing. The fact shows that since their emergence, big data techniques are changing very fast. In this paper, we use our experience in developing and maintaining the information security system for Netease as an example to illustrate how those big data systems evolve. In particular, our first version is a Hadoop-based offline detection system, which is soon replaced by a more flexible online streaming system. Our ongoing work is to build a generic real-time analytic system for Netease to handle various jobs such as email spam detection, user pattern mining, game log analysis, etc. The example shows how the requirements of users (e.g., Netease and its clients) affect the design of big data system and drive the advance of technologies. Based on our experience, we also propose some key design factors and challenges for future big data systems.

نتیجه گیری

6. Conclusions and open problems


In this paper, we use the information security system in Netease as an example to illustrate how big data system evolves when users’ requirements keep changing. We start from an of- fline Hadoop system to an online streaming system. Finally, we want to design a generic system that can provide near real-time analytic services for many Netease applications, such as spam detection, game log analysis and social community mining. Based on our experiences, no solution can address all big data problems, especially when 1) data size keeps increasing; 2) more complex user requirements need to be handled; 3) the emergence of new hardware violates the old design; and 4) the old system becomes too complicated for maintenance.


بدون دیدگاه