8th March, 2022
TABLE OF CONTENTS
Identifying a data breach can take a significant amount of time. The chief factor that results in such data loss or exposure is the lack of protection.
The strategy employed to reduce the risk of data loss is called Data Loss Prevention or DLP. Every organization needs to have a Data Loss Prevention plan.
The plan should include all the strategic tools and processes that will foster the avoidance of the company's data loss, mishandling, and access by someone unauthorized. Irrespective of your goal, your focus should be to craft a DLP that incorporates it all, right from protecting customer data, corporate data, and intellectual property.
So, let us look into some DLP best practices.
One of the most crucial aspects of DLP is to identify and classify sensitive data. The task requires you to define how confidential the data is.
Organizations are becoming more data-driven; therefore, some types of data will be more sensitive than others. This is why we must separate sensitive data from non-sensitive data. Segregate the data that is crucial for your business. This segregation would make the risk management process more efficient.
The task of identification and classification should be for all the data that is present in the organization, including the data that you share with your vendors, partners, and third-party platforms. You must also consider the data that you receive from them.
Whatever data flows in or out of the system faces the risk of getting lost. Hence, you must have a panoramic view to avoid missing any data. Once scanning through the organization’s data is accomplished, the next step is to weigh the importance of each data set.
A precise distinction between what data is sensitive and what is not must be forged. Generally, companies keep the data under these four buckets: public, internal-only, confidential, and restricted. However, the distinction will become ground for treating the data differently based on its classification.
Sensitive data must be stored in a different place from the non-sensitive data. The sensitive data must be protected well because the loss of this data can break your organization.
You can also use data encryption to protect your sensitive data. The encryption process takes plain text and turns it into an unreadable format. The unreadable version is called “ciphertext.”
The idea is to protect any confidential data in such a way that even when an unauthorized party discovers it, they will not be able to decipher it.
All the important business data must be encrypted irrespective of whether the data is at rest (during storage) or in transit (passing through a network). Portable devices must use encrypted disk solutions to keep any sensitive data secured.
You can encrypt the hard drives of all the employees’ computers, laptops, and other devices. This will help in avoiding the loss of important information even if someone gains access to your organization’s devices.
One of the most basic methods to encrypt the data on a Windows system is Encrypting File System technology or EFS. Under this technology, the EFS decrypts the file whenever an authorized user opens an encrypted file to give the actual data. Authorized users can also see or change the file, and EFS saves changes easily as encrypted data. The authorized viewers will receive an "Access denied" error, and if they somehow gain access, they will only receive encrypted data.
You can deploy role-based access control (RBAC) to restrict the access of networks based on an individual’s role in an organization. RBAC is considered one of the main methods for forging advanced access controls within an organization.
The roles must be clearly defined for each individual. The roles generally fall under these categories: end-user, analyst, billing user, admin, and super admin. You must also specify who is the data owner, which IT officer handles which aspect of security incident investigation, and so on.
The RBAC is based on three primary rules that must be followed for successful deployment. These are:
Role assignment - In this, the task of assigning the roles d is done to grant permissions according to the roles.
Role authorization - In this, the authorization is given to the roles to ensure particular individuals are given access to particular information.
Permission authorization - In this, the individual can only use a particular data only if the permission is authorized.
If the majority of the DLP processes are automated, you could easily deploy them across the organization. However, manual DLP processes have a limited scope. They cannot be scaled to meet the requirements of even small IT environments.
The task of automating data handling, notice, consent, and regulatory obligations can help in automating data policy management. The risk of non-compliance is much higher in manual methods.
Automation allows sensitive data, like the location of doubtful login attempts to be tracked without requiring a costly and time-taking campaign.
An enterprise need not write a code and still receive detailed login records. The whole ordeal of automation is free of human errors. The task of switching to automation from the manual processes is also quite easy.
While making a firm DLP policy is quite important, it is not enough. You need to make all the stakeholders and data users aware of the policy and its intricacies. They must properly understand the details of the policy and what their role is in safeguarding the data present within the organization.
No matter the kind of policy you employ, the true prevention of data loss will only be accomplished when data users understand the nitty-gritty details appropriately. Certain sessions and programs can be conducted within the organization that informs all the stakeholders about the data.
Once you establish your DLP policy, the next task is to fix certain key metrics to track. These metrics should help you measure the effectiveness of the DLP strategy you have used.
Some of the metrics you can track are:
Percentage of false positives: One of the greatest challenges of a DLP program is to deal with false positives. A good DLP policy aims at reducing the false positives within your organization. This metric helps in indicating whether your data is effective enough or not.
Mean-time to respond to DLP alerts: The mean-time to respond and initiate the action to DLP alerts with respect to the possible data exfiltration attempt.
The number of unmanaged devices in your network with sensitive data is the number of unmanaged devices that process and store sensitive data. This could include file shares, servers, endpoints, etc.
While there must be a classification between necessary and unnecessary data, there should also be a classification enlisting unnecessary data.
The data enlisted as unnecessary must be eliminated as it is occupying space that can be devoted to an important set of data.
Such data might not contribute much to your organization, but the leaking of such data can be detrimental to the organization. And removing this data can ensure that it is never lost; after all, things that do not exist cannot be lost.
This is one of the most important best practices for efficiently implementing a DLP program. This practice will ensure that there never comes a time when you can just go ahead and say the job is done.
For as long as data is there, the job of protecting and preventing its loss will be there. However, the particular implementation of the DLP strategy must align with and reflect the evolution of your business. As your business grows, the prevention of data loss plan must change the shape too. The policies and procedures should be such that they address the needs of your business in the current times.
It is only through strong DLP programs can a company prevent such a disaster from happening. With the best practices mentioned in this article, you can make a foolproof DLP program for your organization and secure all your data without much hassle.
In this post, we've discussed 7 symptoms of an unoptimized SaaS stack and solutions to optimize the same.
In this post, you'll learn about shadow IT due to SaaS apps. You'll also learn the most common types of shadow apps categories, shadow IT risks, and shadow IT benefits.
An obese SaaS stack leads to SaaS wastage. It's a disease! It not only causes financial issues but also gives you security and compliance problems. That's why you must keep tight control on your SaaS stack. And it begins with managing your SaaS vendors.
When an organization has a large number of SaaS applications in its SaaS stack, it gives rise to SaaS Sprawl.
SaaS operations consist of procuring the right set of SaaS apps, managing access to these apps by users/departments, monitoring their usage, and offboarding them properly when they are no longer needed.
The GRC tools are not one-size-fits-all kinds of stuff. A wide range of products and solutions are available in the market to meet the requirements of various kinds of businesses. Because of this, choosing a perfect GRC tool can be a little difficult for you.
The main purpose for implementing user provisioning is for security and compliance. But in the SaaS world, there are much more shadow apps than those bought by the IT and procurement teams.
SSO can be an asset if used rightly. They make organizations secure and save employees time logging in and out of different apps. But the same can become a liability when performed without a complete understanding of SSO implementation and management. The way to flawless implementation of SSO is easy once you grasp the best practices involved with the usage and implementation.