یک روش طبقه بندی موثر برای امنیت کلان داده ها بر اساس شبکه GMPLS / MPLS An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks

1. Introduction Big data is a new term that refers not only to data of big size, but also to data with unstructured characteristic types (i.e., video, audio, unstructured text, and social media information). Te demand for solutions to handle big data issues has started recently by many governments’ initiatives, especially by the US administration in 2012 when it announced the big data research and development initiative [1]. Te initiative aims at exploring proper and efcient ways to use big data in solving problems and threats facing the nation, government, and enterprise. It is also worth noting that analyzing big data information can help in various felds such as healthcare, education, fnance, and national security. Potential challenges for big data handling consist of the following elements [3]: (i) Analysis: this process focuses on capturing, inspecting, and modeling of data in order to extract useful information. (ii) Treatment and conversion: this process is used for the management and integration of data collected from diferent sources to achieve useful presentation, maintenance, and reuse of data. (iii) Searching: this process is considered the most important challenge in big data processing as it focuses on the most efcient ways to search inside data that it is big and not structured on one hand and on the timing and correctness of the extracted searched data on the other hand. (iv) Storage: this process includes best techniques and approaches for big data organization, representation, and compression, as well as the hierarchy of storage and performance. (v) Visualization: this process involves abstracting big data and hence it helps in communicating data clearly and efciently. (vi) Security and sharing: this process focuses on data privacy and encryption, as well as real-time analysis of coded data, in addition to practical and secure methods for data sharing. Te increasing trend of using information resources and the advances of data processing tools lead to extend usage of big data. Te extensive uses of big data bring diferent challenges, among them are data analysis, treatment and conversion, searching, storage, visualization, security, and privacy. Big data security and privacy are potential challenges in cloud computing environment as the growing usage of big data leads to new data threats, particularly when dealing with sensitive and critical data such as trade secrets, personal and fnancial information. Any loss that could happen to this data may negatively afect the organization’s confdence and might damage their reputation. Moreover, moving big data within diferent clouds that have diferent levels of sensitivity might expose important data to threats.