Solution
Kuldeep answered on
Aug 20 2020
Running head: Big data security and privacy
Big data security and privacy
Big data security and privacy
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Abstract
Today, big data is everywhere. Big data contain tremendous value moreover opportunities. But, big data
ings several security threats or privacy problems. Privacy and Security problem are amplified by speed, quantity or various big data. After that, a traditional safety mechanism is not co
ect for big data safety. The Privacy protections are one of the major challenges of big data. This article includes an explanation and assessment of recent trends in emerging technologies and innovations; a critical analysis of literature search and big data security and privacy literature.
Contents
Abstract 2
Introduction 4
Research problem overview 4
Applications of technology 5
About technology 5
Research issues 6
Related work 6
Proposed solutions to solve the research 7
Experimental analysis 7
Conclusion 8
Recommendations 8
Annotated Bibliography 9
Task 2 15
References 16
Introduction
The concept of privacy varies greatly depending on the country, religion, culture and legal background. In general, privacy refers to sensitive information such as personal wages, patient records, as well as company economic data. However, for various data or information owners, definition of the privacy can also vary. Such as, the conservative patient will treat the data they may have as personal privacy, but patients with open minds may not think so. Generally, right to be exempt from covert surveillance and to determine if, when, how and to whom to disclose personal organizational information.
Research problem overview
This is a relevant party that needs to be addressed by users to share more personal data and content into social networks and public networks through their devices and computers. Therefore, the social network's security plans are very hot topic. The last topic was a case study in two areas of this chapter. In addition, traditional methods of supporting security such as firewalls and military concu
ency areas are not suitable for use in computing systems to support big data. SDN is an emergency management solution that can be a convenient way to implement big data system security, as shown in the second case study at the end of this chapter. It also discussed cu
ent staff and identified unresolved issues. Increasing the amount of data collected, processed, and processed by increasing the number of connected devices and interconnecting each other presents new challenges for privacy and security.
In fact, presently use security systems (for example Firewalls or DMZs) cannot be use in large data infrastructures as it must be extended beyond the perimeters of organization's network to meet security mechanism / data mobility needs or BYOD policies (on their personal device). . Considering this latest solution, the related problem is that security or privacy policy as well as technologies is useful in meeting today's most important data security and privacy challenges. These challenges can be protected for example infrastructure safety (securely distributed computing using MPRADUS), information privacy (such as data mining’s for privacy / donor access) and information management (such as secure data sources as well as storage). An integrity or feedback security (such as i
egular and real-time inspections of attacks)
Applications of technology
The main purpose of large data applications is to help businesses makes more informed-rich company decisions by recognizing large numbers of information, including Web server log, Internet click data stream, media content as well as activity report, text in client’s email, mobile phone call details or capture by many sensors.
Big Data provides comprehensive facilities for services like government agencies, electricity checks, misleading identities, fitness internet exploration, financial incentives, and environmental ba
iers. In today's world, big data is needed. Most people connect with each other through different communication methods. People share information in different ways The amount of information connecting to the population is increasing, creating security and privacy issues. It also creates a location for the rapid development of large data technology, security and privacy issues. As long as these problems are not answered properly, it can create obstacles for large data and expected growth and can achieve long-term success.
About technology
Big data processing creates new opportunities due to its analytical ability. In the business sector big data can benefit from analyzing large numbers of data, the automotive industry, energy distribution industry, healthcare and retail. Examples of this area are the use of consumer purchase history to analyze the search engine queries to find out the out
eak of firewalls to analyze the driving behavior discrepancy using energy grid data and the use of consumer purchase history to generate driving estimates. However, all these examples have data related to the person, so that the underlying data becomes potentially sensitive. Any emergence of the risk shows a privacy and security vulnerability. Data is the most important part of large data. Therefore data protection and data protection between data conversion and privacy implementation is a major requirement for large data.
Research issues
Over the past fifteen years, many technologies have been proposed to ensure data privacy and privacy protection. From encryption technology, for example forgotten data structure in data anonymization technology, in undercover data access mode, data is more difficult to change. Add specific data record for specific people, as well as advanced access controlled models. Nevertheless, several research challenges have been resolved. In the following, we will discuss some. There are many data privacy technologies and mechanisms - mostly access control moreover encryption. Both also have been extensively researched. The option to protect data privacy is a core module for protecting confidentiality, while investigating more relevant cases is necessary in order to protect large data privacy.
Related work
It is necessary to understand how to recognize large data security and confidentiality challenges, as well as how to protect traditional security mechanisms, designed to protect small amounts of static data, largely due to the large number of complex structured and unorganized data stored. Unfair access to this data to make new information, gathering various data sources or making them available to malicious users is a serious threat to large data. The common or basic means for these are to encrypt all to secure information, even where the data live (computer, data center, and mobile devices). As a large number of data increases and processing speed increases, masking, encryption, or tokenization are important factors to protect sensitive information. Due to its features, large data project want to achieve a holistic view of...