Large Collection of Data: Secure Big Data Essay

One consequence of data classification is the need for a tiered storage architecture, which will provide different levels of security within each type of storage, such as primary, backup, disaster recovery and archive -- increasingly confidential and valuable data protected by increasingly robust security. The tiered architecture also reduces costs, with access to current data kept quick and efficient, and archived or compliance data moved to cheaper offline

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

New organizations can leverage Big Data in such a way that it provides benefits that can prove valuable especially to an organization seeking to establish itself and grow. One of these benefits is faster and better decision making. Particularly with the analytics of Big Data, organizations have access to real-time data

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

The main issue that slows down the growth of cloud computing is security. No matter how many security management tools are released or assurances of reliability are made, complications with data privacy and data protection continue to plague the market. Covering all potential security issues in this article is simply impossible. This is because of the fact that we 're still discovering many of the security issues which challenges cloud computing as it is still a work-in-progress. Cloud Computing is rapidly evolving and hence what we see today may quickly become irrelevant.

The industry is inundated with articles on big data. Big data news is no longer confined to the technical web pages. You can read about big data in the mainstream business publications such as Forbes and The Economist. Each week the media reports on breakthroughs, startups, funding and customer use cases. No matter your source for information on big data, one thing they all have in common is that the amount of information an organization will manage is only going to increase; this is what’s driving the ‘big data’ movement.

Big Data. What is big data? As it becomes a more relevant part of the business world, this report covers how to use it, what its benefits are, and what fields it works well in.

This report aims to identify the most common current threats to secure information in the cloud and the most common vulnerabilities that are exploited in order to realize those threats. Recommended controls to mitigate the risks of these threats being realized will be provided for consideration.

Big Data refers to the large amounts of data that businesses deal with on a day-to-day basis. Big Data can be defined in many ways, but this is one of the most general definitions. One of the primary uses businesses have for Big Data is to provide assistance for decision making. In order for Big Data to be effective, organizations must utilize the data to their advantage. The quality of information is what matters, not the quantity. Organizations may have virtually unlimited amounts of data to work with, but they must locate the helpful portions of data in order for it to be effective and serve its purpose. In addition, some data may not be helpful at the present moment in time, but will be needed for analysis in the future (“What Is Big Data?”,

In 2012, the concept of ‘Big Data’ became widely debated issue as we now live in the information and Internet based era where everyday up to 2.5 Exabyte (=1 billion GB) of data were created, and the number is doubling every 40 months (Brynjolfsson & McAfee, 2012). According to a recent research from IBM (2012), 90 percent of the data in the world has been created in the last two years alone, and Internet activity in each second today will generate more data than all the data combined in the

The ever growing need for the data in Information technology organizations has always lead to invent new services to meet the data needs, whether it is in the form of software, platform, hardware or storage. Cloud computing provides this services to organizations with cost effective methodologies like pay per service, network access, on-demand self-service. Organizations no more have to worry about storage overhead. This services has made huge impact on the organizations business process (Q. Wang, C.Wang, and Ren) (2011). At the same time with increase in technological services, the ever growing services are restricted due to security. Organizations use storage as a service to store their data remotely over cloud however the security of data is not guaranteed which leads to problems like data integrity, data availability, and data correctness. Various models has been proposed to address this data integrity concern over cloud (Chakraborty, Dhami, bansal), (2013).

Planning for an effective storage solution, whether it is on premise or off premise can be a challenging task. Off premise planning becomes more complicated as the components that make up the storage network are generally in the control of the cloud provider. It becomes critical to maintain the integrity and security of the data, while still offering a seamless storage solution to the business. The business user does not care where the data is located, or where an application is hosted. It must be available as needed, with little to no noticeable performance degradation.

The guidance provided herein is the third version of the Cloud Security Alliance document, “Security Guidance for Critical Areas of Focus in Cloud Computing,” which was originally released in April 2009. The permanent archive locations for these documents are: http://www.cloudsecurityalliance.org/guidance/csaguide.v3.0.pdf (this document) http://www.cloudsecurityalliance.org/guidance/csaguide.v2.1.pdf (version 2 guidance) http://www.cloudsecurityalliance.org/guidance/csaguide.v1.0.pdf (version 1 guidance) In a departure from the second version of our guidance, each domain was

However, "Big Data" suggests something more than just an analysis of huge volumes of information. The problem is not that the organizations create high volume of data, but the fact that most of them are presented in a format consisting with traditionally poor structured form of database such as: a web-based magazines, images, videos, text documents, machine code and geospatial data . All of these are allocated in a distributed storages, sometimes even

The paper ‘Log file 's centralization to improve cloud security’ proposes a centralized, secure and comprehensive architecture for log-based analysis for cloud computing platform [3]. It suggests the use of logs generated by cloud due to different activities performed, defining the policies of which log file should be kept and which files must be transferred, and reporting of the attacks and threats and attacks based on the analysis of these logs. Algorithms like map-reduce are applied which can report about the patterns which can lead to attacks based on comparison with the stored values. Updating the policies based on the new findings during the analysis of the logs files.