Tips for securing your Big Data

               In IT industry Big Data is a collection of large data sets which are hard to manage on hand base management tools. Some of the challenges faced in managing big data are storage, curation, capture, analysis, visualization and search. Big data are difficult to manage using desktop packages, instead massive software running on several tens or thousands of servers. Demand for maintaining big data has increased especially in the field of telecommunication and IT. Some of the big data maintaining giants are IBM, HP, SAP, Oracle Corporation and Microsoft. Following are some of the tips which I came across for securing big data.

Plan about Securing Data before Starting Big Data Project

                Technicians should involve in protecting big data before installing or feeding data. Organizations need to find alternative ways to secure big data. Organizations should have serious discussions about data security and other related security issues.

Have A Clear Idea About What Data May Get Stored:

                Data incorporated into Hadoop for storing and running are subjected to specific security measures. Every organization faces huge risk or implementing security for data transfer and usage. So companies need to have a look at revenue loss and risk associated with leakage.

Centralize your account:

                Data are organized so vividly, sometimes data reside in diverse organizations. To ensure consistency in data access and for better policy enforcement, centralize the data account.

Separate Encrypted Data and Encryption Keys:

                Maintaining same server for storing both encrypted data and encryption keys is like locking the door and leaving the keys in lock socket. Key management system will allow users to store encryption keys and encrypted data separately.

Use Encryption for Both Data in Motion and At Rest:

                If companies plan to implement SSL encryption, this can protect data as it moves from applications and nodes. Encryption of data will protect malicious administrators or users to gain access to data. This is one of the cost effective ways to solve several data security threats.

Use Secure Automation:

                If you are dealing with the multiple node environments, this might hamper deployment consistency. So it’s better to use automation tools which help you to configure the application, update the stack, certificates, patching and platform.

Use Kerberos Network Authentication Protocol:

                This is one of the effective methods for keeping rouge nodes and application of your cluster. This protocol can help to protect web console access. Kerberos is a painful method to set-up and re-validate new nodes and applications.

Add Log Files To your Cluster:

                Many companies started big data to maintain log files, why not to include log files on-to your clusters? Adding log files will provide you a place to look when you think you have been hacked or when something fails.

Ensure Secure Connectivity Between Nodes and Between Nodes and Applications:

                One of the best methods to ensure secure connectivity is by implementing SSL-TLS. If an organization implements an average built network then it is recommended to integrate the system with stack application.

                Do you agree to these steps, will these steps will help to viagra sale/a> secure big data in an organizational level.

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