Protect digital assets with DLP (Data Loss Prevention)

Updated: Oct 29


What is Data loss prevention (DLP)?Gartner, defines DLP as technologies which perform both content inspection and contextual analysis of data sent via messaging applications such as email and instant messaging, in motion over the network, in use on a managed endpoint device, and at rest in on-premises file servers or in cloud applications and cloud storage.

Data is one of the most important things for any organization; it represents the past, the current and the future of the organization. Data loss means that the organization has some events in the company which can’t be accounted for or a copy of some data is in the wrong hands.


Why is Data Loss Prevention Important:


1. The Brand of an organization is affected:


When a third party claims to have your data or exposes it to the public, the perception is that the security of the organization is weak. Clients and business partners lose faith in the future of working with the brand. Clients may end up terminating business and partners canceling contracts. It would take a lot of effort to reclaim the brand’s lost glory.


2. Compliance with industry and government regulations.


Data is protected by many laws to ensure that data is protected from unlawful use or access. The following or some of the laws:

  • Data Protection Act. (Kenyan)

  • HIPAA (Health Insurance Portability and Accountability Act)

  • GDPR (General Data Protection Regulation)

  • PCI DSS (Payment Card Information Data Security Standard)

  • CCPA (California Consumer Privacy Act)

  • PIPEDA (Personal Information Protection and Electronic Documents Act)


3. Protecting proprietary information

Proprietary information refers to any confidential data or knowledge about an organization. This may include business structure and operations, source code of an application, clients' details and partners details.

Loss of proprietary information may lead to exposure of innovations, which is very core to production organization. Business future plans when lost would give your competitors an edge. If network flows diagrams are exposed, the company would be at risk of a network security bleach.


Steps to Achieve an Effective Data Loss Prevention.

  • Data Identification:


This is the process used to identify the data in the organization based on a criterial used to categorize data. It seeks to discover where sensitive data is located and who has access to the sensitive data.




  • Data Leak Identification:

This process is used to identify areas in the organization where data has been misappropriated. This is where data is either has been lost or is misplaced within an organization. It also discovers the areas of compromise in the organization.

  • Data-in-Motion DLP:

This process ensures that all the data in transit is protected from loss. This includes data on emails, data transfer applications and across the network.

  • Data-at-Rest DLP:

This process ensures that all the data in the storage locations is protected from loss. This includes databases or file sharing systems. It is used to protect against unauthorized access of data or data mining malwares.

  • Data-in-Use DLP:

This process ensures that all the data that is currently in use in the organization is protected from harmful interaction either by a user or an application acting on the data. This interaction may include screen capture, copy/cut/paste or printing.


Data Loss Prevention Best Practices.

  • Educate your employees.

Employees are the ones who interact with data to do their responsibility in the organization. The employees should be educated on how to handle each and every data, to prevent loss without having prior knowledge.



  • Establish data handling policies.

Policies make it easier for employees to understand and also follow the recommended data procedures in an organization. It also make it very easy to follow up a violations against the policy.

  • Create a data classification system.

Data classification helps to place your several types of data with the level of sensitivity and also the threat associated with its loss. This classification allows an organization to clearly separate data of different types.

  • Monitor sensitive data.

After classifications, the sensitive data need to be monitored closely. This involves where it is stored, who has access to it and how is it transferred.

  • Implement a DLP solution.

With the above factors in place, a DLP solution is important as it automates the policies and the classifications. It blocks unauthorized data movements and also gives reports and alerts to administrators.

  • Adopt companion tools of DLP.

DLP is best used when accompanied by other solution like Endpoint solutions, Email solutions, cloud solutions among others. This makes helps to prevent other areas of compromised like malwares, ransomwares among others.


Ways to Classify Data There are four classifications levels for data:

  1. Public data: This type of data is freely accessible to the public. It may include marketing and website data.

  2. Internal-only data: This type of data is strictly accessible to internal company personnel. They may include memos and business strategies.

  3. Confidential data: This data may include Social Security numbers or cardholder data. This data is protected by Data Laws.

  4. Restricted data: Proprietary information, research and data protected by regulations. This data are core business information.

Ariel Technology has for some years partnered with some of the leading IT security vendors so that we can provide you with the world standard DLP solutions you need for your organization.


Our DLP Solutions:

SYMANTEC


Data Loss Prevention Core Solution.