The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic. Download Full-Text PDF Cite this Publication. Using of data-carrying technique, Multiprotocol Label Switching (MPLS) to achieve high-performance telecommunication networks. IEEE websites place cookies on your device to give you the best user experience. The first part challenges the credibility of security professionals’ discourses in light of the knowledge that they apparently mobilize, while the second part suggests a series of conceptual interchanges around data, relationships, and procedures to address some of the restrictions of current activities with the big data security assemblage. Based on the DSD probability value(s), decision is made on the security service? Nevertheless, securing these data has been a daunting requirement for decades. 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. 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 effect of labeling implementation on the total nodal processing time for big data analysis has been shown in Figure 6. In [3], the authors investigated the security issues encountered by big data when used in cloud networks. Figure 4 illustrates the mapping between the network core, which is assumed here to be a Generalized Multiprotocol Label Switching (GMPLS) or MPLS network. Our proposed method has more success time compared to those when no labeling is used. Jain, Priyank and Gyanchandani, Manasi and Khare, Nilay, 2016, Big … 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. The type of data used in the simulation is VoIP, documents, and images. The proposed security framework focuses on securing autonomous data content and is developed in the G-Hadoop distributed computing environment. The VPN capability that can be supported in this case is the traffic separation, but with no encryption. Therefore, we assume that the network infrastructure core supports Multiprotocol Label Switching (MPLS) or the Generalized Multiprotocol Label Switching (GMPLS) [25], and thus labels can be easily implemented and mapped. This has led human being in big dilemma. 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. Future work on the proposed approach will handle the visualization of big data information in order to provide abstract analysis of classification. (v)Visualization: this process involves abstracting big data and hence it helps in communicating data clearly and efficiently. Big Data is a term used to describe the large amount of data in the networked, digitized, sensor-laden, information-driven world. 52 ibid. An internal node consists of a Name_Node and Data_Node(s), while the incoming labeled traffic is processed and analyzed for security services based on three factors: Volume, Velocity, and Variety. 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. Here, our big data expertscover the most vicious security challenges that big data has in stock: 1. (iv)Using labels in order to differentiate between traffic information that comes from different networks. The role of the first tier (Tier 1) is concerned with the classification of the big data to be processed. Among the topics covered are new security management techniques, as well as news, analysis and advice regarding current research. Google Scholar. However, in times of a pandemic the use of location data provided by telecom operators and/or technology … 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. Security Issues. Sectorial healthcare strategy 2012-2016- Moroccan healthcare ministry. 18 Concerns evolve around the commercialization of data, data security and the use of data against the interests of the people providing the data. These security technologies can only exert their value if applied to big data systems. 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. I. Narasimha, A. Sailaja, and S. Ravuri, “Security Issues Associated with Big Data in Cloud Computing,”, S.-H. Kim, N.-U. Each node is also responsible for analyzing and processing its assigned big data traffic according to these factors. The main improvement of our proposed work is the use of high speed networking protocol (i.e., GMPLS/MPLS) as an underlying infrastructure that can be used by processing node(s) at network edges to classify big data traffic. If the traffic has no security requirements, or not required, the gateway should forward that traffic to the appropriate node(s) that is/are designated to process traffic (i.e., some nodes are responsible to process traffic with requirements for security services, and other nodes are designated to process traffic data with no security requirements). Tier 1 is responsible to filter incoming data by deciding on whether it is structured or nonstructured. Forbes, Inc. 2012. (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. In addition, the simulated network data size ranges from 100 M bytes to 2000 M bytes. The method selectively encodes information using privacy classification methods under timing constraints. (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. The current security challenges in big data environment is related to privacy and volume of data. The main components of Tier 2 are the nodes (i.e., N1, N2, …, ). The current security challenges in big data environment is related to privacy and volume of data. . CiteScore values are based on citation counts in a range of four years (e.g. This approach as will be shown later on in this paper helps in load distribution for big data traffic, and hence it improves the performance of the analysis and processing steps. Copyright © 2018 Sahel Alouneh et al. Accordingly, we propose to process big data in two different tiers. Big data security in healthcare Healthcare organizations store, maintain and transmit huge amounts of data to support the delivery of efficient and proper care. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. Classifying big data according to its structure that help in reducing the time of applying data security processes. 32. However, Virtual Private Networks (VPNs) capabilities can be supported because of the use of GMPLS/MPLS infrastructure. In Section 4, the validation results for the proposed method are shown. Big Data and Security. They proposed a novel approach using Semantic-Based Access Control (SBAC) techniques for acquiring secure financial services. Authentication: some big data may require authentication, i.e., protection of data against modification. Data classification detection success time of IP spoofing attacks. The first algorithm (Algorithm 1) decides on the security analysis and processing based on the Volume factor, whereas the second algorithm (Algorithm 2) is concerned with Velocity and Variety factors. Large volumes of data are processed using big data in order to obtain information and be able 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 … Big data is becoming a well-known buzzword and in active use in many areas. 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. Analyzing and processing big data at Networks Gateways that help in load distribution of big data traffic and improve the performance of big data analysis and processing procedures. The type of traffic used in the simulation is files logs. The study aims at identifying the key security challenges that the companies are facing when implementing Big Data solutions, from infrastructures to analytics applications, and how those are mitigated. 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. Figure 5 shows the effect of labeling on the network overhead. Why your kids will want to be data scientists. In other words, this tier decides first on whether the incoming big data traffic is structured or unstructured. Therefore, a big data security event monitoring system model has been proposed which consists of four modules: data collection, integration, analysis, and interpretation [ 41 ]. The network overhead is here defined as the overhead needed to communicate big data traffic packets through the network core until being processed by edge node(s). The report also emphasizes on the growth prospects of the global Big Data Network Security Software market for the period 2020-2025. (2018). Tier 2 is responsible to process and analyze big data traffic based on Volume, Velocity, and Variety factors. This is a common security model in big data installations as big data security tools are lacking and network security people aren’t necessarily familiar with the specific requirements of security big data systems. Possibility of sensitive information mining 5. Variety: the category of data and its characteristics. Google Scholar. In the Tier 1 structure shown in Figure 2, the gateway is responsible for categorizing the incoming traffic into labels called labeled traffic (Lm). The simulations were conducted using the NS2 simulation tool (NS-2.35). Sensitivities around big data security and privacy are a hurdle that organizations need to overcome. The analysis focuses on the use of Big Data by private organisations in given sectors (e.g. It is really just the term for all the available data in a given area that a business collects with the goal of finding hidden patterns or trends within it. On the other hand, handling the security of big data is still evolving and just started to attract the attention of several research groups. For example, if two competing companies are using the same ISP, then it is very crucial not to mix and forward the traffic between the competing parties. In addition, authentication deals with user authentication and a Certification Authority (CA). 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