Key Program Metrics of Data Loss Prevention

Data Loss Prevention is a set of security controls that helps organization protect their sensitive data, throughout its life cycle, across all platforms, from getting disclosed to unauthorized users (insiders or outsiders) either accidentally or intentionally.
Different types of DLP:
  1. Endpoint DLP: Protects data leak from endpoints devices such as, data leak from removable storage devices (USB’s), Local file shares, print services etc. Endpoint DLP controls data usage on laptops, workstations, servers and provides additional layer of protection for Mobile users.
  2. Network DLP: Provides broad security coverage across networks.  Network DLP is able to perform deep packet inspection across applications, Protocols and are able to monitor SSL/ and other forms of encrypted traffic. They are content aware and uses myriad set of rules and policies to monitor data in Motion.
  3. Storage DLP: Protects data stored on Storage towers and network storage. Helps in data discovery, data classification and data de-duplication.  Enforces sensitive data storage policy across all devices and networks.
  4. Cloud DLP: DLP functionality extended to the cloud. This is for the protection of your cloud apps or if you have sensitive data residing on the cloud. Cloud based DLP also has an additional advantage of being deployed in the more speedy and cost effective way. Cloud Access Security Brokers (CASB) provides Cloud DP features in addition to other security features.

Let’s have look at some of the key program metric of Data Loss Prevention (DLP) Technology:

Key Program Metrics:

#Exceptions granted during defined time period :
This is the number of exceptions granted over a defined time period. Exceptions are temporary permissions granted on a case-to-case basis. If the Exceptions are not tracked or documented these could result in potential vulnerabilities for exploitation. Ideally, the number of exceptions for a defined time period should remain as minimum as possible

# False positives during defined time period :
One of the major challenges in Data Loss Prevention program is dealing with false positives. Any mature DLP program within an organisation will try to reduce the false positives to near zero value. This metric is a very good indicator of your Data classification effectiveness, DLP rule-set effectiveness etc.

Mean time to respond to any attempted data breach :
This is the mean time to respond and initiate action to DLP alerts regarding possible data exfiltration attempt. This metric is important as most DLP implementations are for alerts only and aren’t put into Blocking mode due to high False-positives. DLP alerts are among the most significant security events those Data if not prioritized can result in a major data breach. DLP alerts can uncover malicious insider attacks, advance persistent threats and accidental data breach.

# Mis-managed devices in your network handling sensitive data :
This is the number of mis-managed devices which processes and stores sensitive data. This could be file shares, endpoints, servers etc. Each of these devices is potential egress points for sensitive data. A good DLP program will have all of the devices, that handles sensitive data, managed using DLP tool.

# Databases not yet fingerprinted :
Database fingerprinting is one of the key methods which any modern DLP tool use to protect your sensitive data against possible leakages. Ideally, all the databases holding sensitive data must be fingerprinted and available to the DLP tool. This metric gives an indication of the risks associated with databases which are yet to be fingerprinted.

# Databases and data residents not yet classified :
The first step in any Data Loss Prevention program is data classification. Data classification is done to identify sensitive data wherever it resides. It is imperative to classify databases and other data resident devices so that effective controls can be applied to them. If you are blind about your sensitive data sources your DLP is already a failure. This metric indicates you the number of databases, devices, endpoints, file shares which are still at your blind spots.

Do let me know if you want us to add or modify any of the listed key use cases.

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