The employed protocol as a routing agent for routing is the Open Shortest Path First (OSPF), while the simulation takes into consideration different scenarios for traffic rate and variable packets sizes, as detailed in Table 1. Nevertheless, traffic separation can be achieved by applying security encryption techniques, but this will clearly affect the performance of the network due to the overhead impact of extra processing and delay. This special issue aims to identify the emerged security and privacy challenges in diverse domains (e.g., finance, medical, and public organizations) for the big data. 51 Aradau, C and Blanke, T, “ The (Big) Data-security assemblage: Knowledge and critique ” (2015) 2 (2) Security Dialogue. However, the algorithm uses a controlling feedback for updating. https://data.mendeley.com/datasets/7wkxzmdpft/2, Function for getting Big Data traffic by Name_node, (i) Real time data is assigned different label than file transfer data and, thus the label value should indicate the Volume size. Share. 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 financial information. Our assumption here is the availability of an underlying network core that supports data labeling. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Even worse, as recent events showed, private data may be hacked, and misused. However, it does not support or tackle the issue of data classification; i.e., it does not discuss handling different data types such as images, regular documents, tables, and real-time information (e.g., VoIP communications). Moreover, the work in [13] focused on the privacy problem and proposed a data encryption method called Dynamic Data Encryption Strategy (D2ES). The GMPLS extends the architecture of MPLS by supporting switching for wavelength, space, and time switching in addition to the packet switching. (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. Moreover, it also can be noticed that processing time increases as the traffic size increases; however, the increase ratio is much lower in the case of labeling compared to that with no labeling. As mentioned in previous section, MPLS is our preferred choice as it has now been adopted by most Internet Service Providers (ISPs). International Journal of Production Re search 47(7), 1733 –1751 (2009) 22. Any loss that could happen to this data may negatively affect the organization’s confidence and might damage their reputation. In the world of big data surveillance, huge amounts of data are sucked into systems that store, combine and analyze them, to create patterns and reveal trends that can be used for marketing, and, as we know from former National Security Agency (NSA) contractor Edward Snowden’s revelations, for policing and security as well. The simulations were conducted using the NS2 simulation tool (NS-2.35). The core network consists of provider routers called here P routers and numbered A, B, etc. (ii) Data source indicates the type of data (e.g., streaming data, (iii) DSD_prob is the probability of the Velocity or Variety data, Function for distributing the labeled traffic for the designated data node(s) with. Simulation results demonstrated that using classification feedback from a MPLS/GMPLS core network proved to be key in reducing the data evaluation and processing time. Kim, and T.-M. Chung, “Attribute relationship evaluation methodology for big data security,” in, J. Zhao, L. Wang, J. Tao et al., “A security framework in G-Hadoop for big data computing across distributed cloud data centres,”, G. Lafuente, “The big data security challenge,”, K. Gai, M. Qiu, and H. Zhao, “Security-Aware Efficient Mass Distributed Storage Approach for Cloud Systems in Big Data,” in, C. Liu, C. Yang, X. Zhang, and J. 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Seker, “Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook,”, Z. Xu, Z. Wu, Z. Li et al., “High Fidelity Data Reduction for Big Data Security Dependency Analyses,” in, S. Alouneh, S. Abed, M. Kharbutli, and B. J. Mohd, “MPLS technology in wireless networks,”, S. Alouneh, A. Agarwal, and A. En-Nouaary, “A novel path protection scheme for MPLS networks using multi-path routing,”. , N1, N2, …, ) t a lot of a move... Short intervals to prevent man in the simulation is VoIP, documents and! And contributors must check their papers before submission to making assurance of following our anti-plagiarism policies –1751 2009... Analysis has been a daunting requirement for decades following our anti-plagiarism policies that. On GMPLS/MPLS networks, audio, video, etc. ) expertscover the most vicious challenges... 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