Defining Data Loss Prevention (DLP)

Data loss prevention (DLP), is a security strategy that allows organizations to control how their sensitive data can be shared across their networks and various endpoint devices. DLP tools identify, monitor and protect data in use (data in motion), at rest (data not being actively used) or in process (data being stored or processed on a system).

These solutions can prevent unauthorized users from accessing intellectual property, customer information and other types of sensitive information, which is especially important given the increasing number of ways sensitive data can be exposed through social media, mobile devices and cloud applications.

Data loss prevention is widely used in industries like healthcare, financial services and government agencies, but it can be used by any company that has sensitive data to protect—including retail businesses, education providers and even individuals who have personal information on their computers or other devices.

How Does DLP Work?

Data loss prevention software can be installed on computers, laptops, and tablets to prevent sensitive data from leaving the device without authorization. It can also be used as part of an email service provider’s security suite to analyze incoming and outgoing emails for sensitive information.

DLP software works by comparing data against a list of rules, or “policies,” that you set up. For example, if you want to prevent employees from sending sensitive information outside the company, you could create a policy that blocks all email attachments larger than 1MB.

You can also create policies based on the content of messages. If your company has confidential information about its clients, it might be best to block certain words like “client” or “confidential.” Once you’ve created some policies for DLP, it will work behind-the-scenes to identify any unauthorized transmissions or storage of sensitive information and prevent them from happening.

Why Do Organizations Need DLP?

They don’t–What organizations do need however, is more modern and intuitive prevention. Many organizations have implemented DLP to help them protect their sensitive data from leaving the company’s control, but many more are considering it because they’re worried about being fined for noncompliance with GDPR regulations.

Oftentimes, prevention is even better than a solution. BigID’s Access Intelligence App helps organizations highlight vulnerable and high-risk data at-a-glance, uncovering overexposed data so you can prioritize remediation efforts to secure it. On top of that, BigID’s Remediation App enables remediation of high risk, sensitive, and regulated data with workflows to delegate decisions to the right people. From there you can mark the right data to annotate, delete, quarantine, tombstone, and more. BigID also allows you to customize remediation actions and policies, report and audit on actions taken on sensitive data for legal and regulatory purposes.

Watch “How to Enrich & Extend DLP with BigID” on-demand webinar.

What Causes a Data Leak?

Data leaks can happen in many ways, but they all have one thing in common: someone has access to your data when they shouldn’t.

Insider Threats

Insider threat is one of the most common causes for data loss and data leaks, where an insider within an organization intentionally leaks sensitive information to unauthorized third parties. Insider threat is any action or event that results in unauthorized access to, disruption of, or destruction of information systems or assets. It can be intentional or unintentional, and it usually involves a trusted employee who has access to sensitive or privileged information.

Cyberattacks

Phishing and malware can also cause data loss and data leaks, as these attacks rely on tricking users into giving up sensitive information such as passwords or credit card numbers. Hackers will try to trick employees into giving them access to company information through the use of emails or websites that appear legitimate but aren’t.

Negligence

Humans are far from perfect, mistakes are not uncommon when it comes to data exposure.
In one study, 76% of respondents had shared confidential data via text message or email at least once during their career; 30% had done so within the past month alone.
Organizations’ use of social media, mobile devices and cloud applications has introduced a number of new vulnerabilities that make it easier than ever for an employee to accidentally share sensitive information with the public.

What Does the Future of DLP Look Like?

Modern problems require modern solutions. The future of DLP may not be DLP at all. Many of today’s DLP solutions are fragmented and offer little consistency. It’s nearly impossible to identify sensitive data when each endpoint, file, network, and cloud require a different set of data loss prevention tools.

BigID allows organizations to accelerate DLP through consistency, coverage, and accuracy while also alleviating the burden on these tools. BigID standardizes sensitivity classification definitions for your organization as a means to consistently enforce policies and controls across all of your data, regardless of where it lives. BigID provides hundreds of OOB classifiers in addition to customizable ML-based classifiers to classify more data, more accurately, and at scale. By confidently finding and classifying your data with precision, BigID enables the pre-remediation of your data as a form of prevention from unauthorized or unintended data leakage.

To find out more about how BigID’s Data Intelligence platform can help bridge the gap between your DLP tools, set up a 1:1 demo with us to see it in action.