In general, big data are collected in real time, typically running into the millions of transactions per second for large organizations. The obtained results show the performance improvements of the classification while evaluating parameters such as detection, processing time, and overhead. The type of traffic analyzed in this simulation is files logs, and the simulated data size ranges from a traffic size of 100 Mbytes to 2000 Mbytes. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. It require an advance data management system to handle such a huge flood of data that are obtained due to advancement in tools and technologies being used. Data security is the practice of keeping data protected from corruption and unauthorized access. Big Data in Healthcare â€“ Pranav Patil, Rohit Raul, Radhika Shroff, Mahesh Maurya â€“ 2014 34. 32. Keywords: Big data, health, information, privacy, security . The two-tier approach is used to filter incoming data in two stages before any further analysis. Share. Potential challenges for big data handling consist of the following elements :(i)Analysis: this process focuses on capturing, inspecting, and modeling of data in order to extract useful information. So instead of giving generic advice about “security,” I want to show you some ways you can secure yourself and … 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. Therefore, header information can play a significant role in data classification. A flow chart of the general architecture for our approach. The new research report titles Global Big Data Network Security Software market Growth 2020-2025 that studies all the vital factors related to the Global Big Data Network Security Software market that are crucial for the growth and development of businesses in the given market parameters. We have chosen different network topologies with variable distances between nodes ranging from 100m to 4000Km in the context of wired networks (LAN, WAN, MAN). The key is dynamically updated in short intervals to prevent man in the middle attacks. Security Journal brings new perspective to the theory and practice of security management, with evaluations of the latest innovations in security technology, and insight on new practices and initiatives. Moreover, it also can be noticed the data rate variation on the total processing with labeling is very little and almost negligible, while without labeling the variation in processing time is significant and thus affected by the data rate increase. In addition, authentication deals with user authentication and a Certification Authority (CA). Please feel free to contact me if you have any questions or comments. The Gateways are responsible for completing and handling the mapping in between the node(s), which are responsible for processing the big data traffic arriving from the core network. In Figure 7, total processing time simulation has been measured again but this time for a fixed data size (i.e., 500 M bytes) and a variable data rate that ranges from 10 Mbps to 100 Mbps. In the proposed approach, big data is processed by two hierarchy tiers. They proposed a novel approach using Semantic-Based Access Control (SBAC) techniques for acquiring secure financial services. In this subsection, the algorithm used to classify big data information (Tier 1) (i.e., whether data is structured or unstructured and whether security is applied or not) is presented. IEEE websites place cookies on your device to give you the best user experience. In the proposed GMPLS/MPLS implementation, this overhead does not apply because traffic separation is achieved automatically by the use of MPLS VPN capability, and therefore our solution performs better in this regard. Classifying big data according to its structure that help in reducing the time of applying data security processes. In addition, the protocol field indicates the upper layers, e.g., UDP, TCP, ESP security, AH security, etc. It is worth noting that label(s) is built from information available at (DH) and (DSD). Data Security. Forbes, Inc. 2012. This has led human being in big dilemma. The MPLS header is four bytes long and the labels are created from network packet header information. However, the proposed approach also requires feedback from the network in order to classify the processed data. Figure 5 shows the effect of labeling on the network overhead. The performance factors considered in the simulations are bandwidth overhead, processing time, and data classification detection success. Sahel Alouneh, Feras Al-Hawari, Ismail Hababeh, Gheorghita Ghinea, "An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks", Security and Communication Networks, vol. Impact Factor: * 3.644 *2019 Journal Citation Reports (Clarivate, 2020) The leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. 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. 18 Concerns evolve around the commercialization of data, data security and the use of data against the interests of the people providing the data. Therefore, header information can play a significant role in data classification. The security and privacy protection should be considered in all through the storage, transmission and processing of the big data. Variety: the category of data and its characteristics. Besides that, other research studies [14–24] have also considered big data security aspects and solutions. Indeed, It has been discussed earlier how traffic labeling is used to classify traffic. Daily tremendous amount of digital data is being produced. The effect of labeling implementation on the total nodal processing time for big data analysis has been shown in Figure 6. Furthermore, in , they considered the security of real-time big data in cloud systems. A flow chart for the general architecture of the proposed method is shown in Figure 1. It can be noticed that the total processing time has been reduced significantly. Another work that targets real-time content is presented in , in which a semantic-based video organizing platform is proposed to search videos in big data volumes. Thus, security analysis will be more likely to be applied on structured data or otherwise based on selection. The growing popularity and development of data mining technologies bring serious threat to the security of individual,'s sensitive information. When considering a big data solution, you can best mitigate the risks through strategies such as employee training and varied encryption techniques. It can be clearly noticed the positive impact of using labeling in reducing the network overhead ratio. The proposed security framework focuses on securing autonomous data content and is developed in the G-Hadoop distributed computing environment. Possibility of sensitive information mining 5. On the other hand, handling the security of big data is still evolving and just started to attract the attention of several research groups. 2018, Article ID 8028960, 10 pages, 2018. https://doi.org/10.1155/2018/8028960. (iii)Transferring big data from one node to another based on short path labels rather than long network addresses to avoid complex lookups in a routing table. To contact me if you have any questions or comments networks ( VPNs ) capabilities can be supported because the... 1733 –1751 ( 2009 ) 22 Bimonthly current volume: the confidentiality is! At the gateway of the proposed algorithms depends on the growth prospects of the generation. Systems and Internet of Things ( IoT ) the big data security journal, digitized, sensor-laden, information-driven world with 8.51. 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