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9 Things Your Competitors Know About Data-centric Security

Data-centric security, at its heart, is just another lock. But what happens when that lock is picked (keys stolen, credentials compromised)? Over the coming quarters, effective monitoring and access analytics will become key to ensuring the success of this promising initiative.

We will see data-centric security becoming more and more relevant and essential over other forms of security. Network security can be compromised, however data security will prevent data that is hacked, from being read.

At the moment, data-centric security is receiving a great deal of attention. However, in higher-risk environments, there is resistance to implementation. This speaks to education and change management that goes beyond next several quarters.

Data-centric approach to security is a double-edged sword. Focus on protecting what needs to be protected can also lead to sprawling complexity if overdone. The best approach is to focus on as few classes of data as possible.

Data-centric security will continue to be a hot area, but the amount of data shown to human analysts will decline. It’s all about machines surfacing the interesting information.

The primary change within Data-centric security will be a trend toward developer targeted Platform-as-a-Service security solutions and away from costly and custom security hardware infrastructure.

As we move increasingly to cloud models, thus releasing control of infrastructure, security providers will focus more on the data itself and how we can manage, classify, and protect it.

In relation to data-centric security we excel at authenticating data users and data encryption, but first we need to go back to the basics of data discovery and classification.

The dual phenomena of cybercrime and big data make it critical that enterprises understand provenance, governance and data management as part of a holistic security story.


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  1. Data-Centric Security, Basically deals with securing sensitive data or information during its Storage, Transfer and End-delivery point.
    In a Money safe or a vault, money is safest due to the least number’s of entry to the storage place. allowing maximum grade security to be applied to the entry. Secondly, During the transfer of money, there is a certain protocol following it to deliver it safely. routes are pre-defined, security personnel is well informed about what protocols to follow when or if they cite any unusual activity. And when the Money is being transferred to the other vault, they are sent in locked boxes.

    Same can be done with the task of protection of data i.e.
    Giving least no. of trusted people direct access to it.
    Providing only one method or mode of data extraction from the source such as Cloud.
    During the transfer process, checks can be made to not allow any other device to be communicating on that network.
    and during the transfer Encryption is already being provided.

    By providing least no. of access points we can reduce the amount of threat it can be under.

  2. As the technology is graduating towards its excellence so as enormous amount of data is being generated and stored. It is becoming tactically difficult for the business firms to facilitate and co-ordinate between the data availability and sharing appropriately and accurately among its own professionals. Thus making the companies to move to the cloud based services to ensure and provide the relevant and needed data with the desired community. But this comes with a lot of unprotected data transfers which is making it vulnerable to data theft and hacking.
    With the technology of Data centric security, the data which is accepted as the most valuable asset of any business firm is getting protected. Not only does this provide data protection but also encryption of the data which helps in making the data unreadable even if hacked.
    Data centric Security facilitates the data transfer easily without compromising its security. With this technology the data is more secured, encrypted and safe.

  3. Data-centric security is a need of the hour in this digital age as everything which is working around us comprises of data,and once it is compromised many unnecessary risks can get invited.To protect our data, measures must be taken to store them in a secure location such that accessibility does not pose a threat as it is checked with higher levels of clearance authority.This secure location can be cloud system which has very less probability to get hacked.Other ways of securing data can be done using cryptography where the data which is being transferred in to the cloud can be end-to-end encrypted so that the data is safe in the package in which it is being transferred.The data which stays in the cloud can also be encrypted such a way that the data stays in an uneven order and does not make sense if it is being viewed on a system through which its being monitored or through which its being hacked,but when an encryption code is entered into the system the data returns to the original form.This encryption code keeps changing every-minute as it is a system generated code.These are some ways where data centric security can be ensured and protected from getting into wrong hands.

  4. Gone are the days when endpoints of the organization were confined to desktops and laptops connected to the LAN and somewhat easy to secure and manage by central IT administrators. Endpoints now included virtual users, smartphones, tablets, external consultants and even partner organizations with a need to exchange information. These additional complexities require information to be pushed and pulled to devices internally and externally, thereby increasing the risk of exposure and the likelihood of data theft.
    It’s a good approach to protect the data rather than the devices at the end-point of an organization.Data-centric security is the only way to ensure the most important asset of the business—the data—is protected.
    Data-centric security is evolving rapidly as enterprises increasingly rely on digital information to run their business and big data projects become mainstream.

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