Furthermore, the proposed classification method should take the following factors into consideration [5]. Big data is becoming a well-known buzzword and in active use in many areas. Big data innovations do advance, yet their security highlights are as yet disregarded since it’s trusted that security will be allowed on the application level. Data Security. Next, the node internal architecture and the proposed algorithm to process and analyze the big data traffic are presented. Big data is the collection of large and complex data sets that are difficult to process using on-hand database management tools or traditional data processing applications. Data Header information (DH): it has been assumed that incoming data is encapsulated in headers. Indeed, our work is different from others in considering the network core as a part of the big data classification process. A flow chart of the general architecture for our approach. In this article, security challenges and concerns of IOT big data associated with smart grid are discussed along with the new security enhancements for identification and authentications of things in IOT big data … The network core labels are used to help tier node(s) to decide on the type and category of processed data. Finance, Energy, Telecom). 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. So, All of authors and contributors must check their papers before submission to making assurance of following our anti-plagiarism policies. 32. Even worse, as recent events showed, private data may be hacked, and misused. This paper discusses the security issues related to big data due to inadequate research and security solutions also the needs and challenges faced by the big data security, the security framework and proposed approaches. Automated data collection is increasing the exposure of companies to data loss. The analysis focuses on the use of Big Data by private organisations in given sectors (e.g. Big Data security and privacy issues in healthcare – Harsh Kupwade Patil, Ravi Seshadri – 2014 32. Now think of all the big data security issues that could generate! The technique analyzes big data by extracting valuable content that needs protection. Nowadays, big data has become unique and preferred research areas in the field of computer science. Online Now. Troubles of cryptographic protection 4. The current security challenges in big data environment is related to privacy and volume of data. As recent trends show, capturing, storing, and mining "big data" may create significant value in industries ranging from healthcare, business, and government services to the entire science spectrum. In [7], they also addressed big data issues in cloud systems and Internet of Things (IoT). This kind of data accumulation helps improve customer care service in many ways. It is also worth noting that analyzing big data information can help in various fields such as healthcare, education, finance, and national security. 12 Big data are usually analyzed in batch mode, but increasingly, tools are becoming available for real-time analysis. However, Virtual Private Networks (VPNs) capabilities can be supported because of the use of GMPLS/MPLS infrastructure. This factor is used as a prescanning stage in this algorithm, but it is not a decisive factor. Total Downloads: 24; Authors : Loshima Lohi, Greeshma K V; Paper ID : IJERTCONV4IS06016; Volume & … All rights reserved, IJCR is following an instant policy on rejection those received papers with plagiarism rate of. GMPLS/MPLS are not intended to support encryption and authentication techniques as this can downgrade the performance of the network. Total processing time in seconds for variable network data rate. The COVID-19 pandemic leads governments around the world to resort to tracking technology and other data-driven tools in order to monitor and curb the spread of SARS-CoV-2. One basic feature of GMPLS/MPLS network design and structure is that the incoming or outgoing traffic does not require the knowledge of participating routers inside the core network. Consequently, the gateway is responsible for distributing the labeled traffic to the appropriate node (NK) for further analysis and processing at Tier 2. In addition, the gateways outgoing labeled traffic is the main factor used for data classification that is used by Tier 1 and Tier 2 layers. Possibility of sensitive information mining 5. The primary contributions of this research for the big data security and privacy are summarized as follows:(i)Classifying big data according to its structure that help in reducing the time of applying data security processes. Therefore, security implementation on big data information is applied at network edges (e.g., network gateways and the big data processing nodes). The 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]. Figure 4 illustrates the mapping between the network core, which is assumed here to be a Generalized Multiprotocol Label Switching (GMPLS) or MPLS network. The security and privacy protection should be considered in all through the storage, transmission and processing of the big data. In addition, authentication deals with user authentication and a Certification Authority (CA). Any loss that could happen to this data may negatively affect the organization’s confidence and might damage their reputation. In related work [6], its authors considered the security awareness of big data in the context of cloud networks with a focus on distributed cloud storages via STorage-as-a-Service (STaaS). Thus, the use of MPLS labels reduces the burden on tier node(s) to do the classification task and therefore this approach improves the performance. Volume: the size of data generated and storage space required. Confidentiality: the confidentiality factor is related to whether the data should be encrypted or not. Big data network security systems should be find abnormalities quickly and identify correct alerts from heterogeneous data. This press … Abouelmehdi, Karim and Beni-Hessane, Abderrahim and Khaloufi, Hayat, 2018, Big healthcare data: preserving security and privacy, Journal of Big Data, volume 5,number 1, pages 1, 09-Jan 2018. Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. 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