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Intelligent Data Loss Prevention – Its Definition And Use in Businesses

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Ugra Narayan Pandey
I am proudly an Indian and Currently working as a Cloud Security Expert with CloudCodes.
There are several data loss prevention software in the marketplace and picking up one is really difficult. Today this particular post is going to describe the exact definition of an intelligent data loss prevention and its use in the business world.

DLP – A Quick Introduction


Data loss prevention technique is a procedure to secure confidential information at rest, on an endpoint, and in-transit mode. It helps in reducing the likelihood of data theft or unauthorized leakage incidents. DLP approaches help in preventing confidential data as well as business private content from being getting used in an unauthorized manner. Cloud DLP methods particularly secure businesses, which are using cloud computing technology to grow. 


These approaches ensure that confidential information will not be able to create its own path online until and unless it is not encrypted and is only received by authentic cloud apps. Many DLP solutions eliminate or alert classified or sensitive content before it gets shared on the cloud. This sort of activity is done to secure information even in rest mode.


An Intelligent Data Loss Prevention Solution


Data Loss Prevention or DLP technology is a set of products and processes, consolidated and implemented to ensure the security of confidential, regulated, sensitive, and business-critical information. It protects core enterprise data from being getting misused, stolen, or made accessible by unauthorized end users. Most DLP technologies are driven by the regulatory compliance requirements enforced by regulations like HIPAA, SOX, FISMA, PCI-DSS, or GDPR. 


An effective data loss prevention application enables users to create standards, which define violations with regards to the use, deletion, and copy of data, and render for multiple operations to be acquired in the violation occasion of more than one predefined standards. The existing operations could be one or more different combinations of warnings, alerts, blocking of the wrong operations, content encryption in doubt state, locking the intruder, and more, with only one goal of limiting or preventing malicious or accidental data sharing that can put the business in regulatory, reputation, or financial risk. 


An intelligent data loss prevention technique holds all rule violations in a log along with several advanced measures offering complete forensics information, comprising of a video recording of the actual occasion and reporting abilities, with the purpose of assisting the forensics, incident management, data breach, and reporting the business requirements.


Large and government business communities from all around the world are undergoing rule changes and are subject to an increased set of information privacy standards. This will demand companies revisiting and improving their security implementations and data privacy rules. On the basis of Privacy Rights Clearinghouse reviews, there have been around 8600 publicly reported data breach incidents since 2005. 


The CyberWorld has created theft activities and leakage measures much easier by making it tougher to achieve Cybersecurity in a substantial manner. The traditional solutions of data loss prevention are to primarily concentrate over the network and file monitoring activity with modern and intelligent data loss prevention software. This product takes a user-centric or an endpoint approach for DLP, consolidating several disciplines like user behavior analytics, user activity monitoring, data loss prevention, and forensics to grow the DLP implementation effectiveness. Also, it enables users to enhance the alignment between technology implementation and enterprise needs. 


These upcoming solutions of DLP have a wider, more capable standards and policy management engine, with the power of monitoring user activity, identifying anomalies beyond the purview of traditional DLP machines, and analyzing user behavior to assign risks in a dynamic manner. All these approaches are primarily focused upon content movement and not on the user actions’ series. For example – a recent activity performed by an employee on the job search website will increase the value of risk score for his / her activities. It is so because it pertains to extract data from the CRM system of a company, triggering a warning to perform further analysis by the compliance team.


Where to Use An Intelligent Data Loss Prevention Software?


Every industry that gathers, stores, and uses Personally Identifiable Information (PII) about their clients or/and employees, collects personal records of EU citizens, collects credit card details etc., is subject to variety of regulations like PCI DSS, GDPR, and HIPAA to store, limit down access, and secure this confidential data from being getting exposed. In addition to all this, enterprises that originate and own their intellectual properties have to implement exact data loss protection and prevention techniques to minimize the challenges of reputation and financial losses in the event of data breaches. Last but not least, a data loss prevention approach can monitor all the movement of data within an organization in an effective manner. It monitors the data access for privileged end users, 3rd party service providers, and the entire population to address unauthorized access or internal attack and hence, stop data leakage.


Data Loss Prevention App For SMBs and Large Companies


Latest policy developments have forced companies to enhance their existing security level with new investments that are made in employee training, refinement of processes, and security technology implementations. With a stronger security standard in place as a new universal company standard, DLP is once again at the top in people's’ minds. Several security experts imagine the renewed concentration on data loss prevention as being driven by the heightened customer awareness of data leakages. This is the cause their requirements have higher data security levels along with an increment in regulatory compliance and substantial penalties for breach. The respective technique drives organizations to enforce, review, and enhance their data privacy as well as security measures with incremental investment in technologies, oversight, and processes of data loss prevention.


Last Few Suggestion Lines


Picking up one intelligent data loss prevention software, installing, configuring, and maintaining it – demands for a substantial, up-front financial slips for a product license, hardware investment, and IT & compliance resources. All these aspects are required to maintain and hold the entire implementation. Most of the SMBs are left exposed with regards to their compliance demands and hence, effective security against accidental and malicious data loss.



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