Cloud Data Loss Prevention Best Practices

How to Prevent Cloud Data Loss

Data loss prevention (DLP) or the protection of sensitive data is a priority for any organization. Protecting and managing data within an organization’s ecosystem means understanding business, regulatory, and infrastructural risks. Preventing exfiltration from cloud services to unauthorized parties is also a priority for some organizations. Organizations that allow third-party providers to access their data should be aware of the risk of exposure and may want to take proactive measures using a cloud-based information security management system (ISMS).

There are many ways sensitive data is exposed in a public cloud environment. In addition, there are many ways cloud service providers protect their infrastructure and the data they store. This paper will discuss the types of data that may be of interest to an attack and how the owner of that information can protect it using a cloud ISMS.

Today, we’re walking you through the best practices you can employ for cloud data loss prevention.

Respect Your Customer’s Privacy

We no longer consider privacy and security to be distinct concepts. The first step in maintaining client data in the cloud is to respect a user’s privacy – the rights they have to manage access to and use of their personal information. 

There’s a reason why, in recent years, governments all over the world have enacted a slew of privacy laws (including the GDPR and the California Consumer Privacy Act) (such as GDPR and the California Consumer Privacy Act). The more data a company collects from a customer, the more information it must protect against bad actors attempting to compromise data security. 

The simplest way is to simply acquire the necessary information from a consumer. Enterprises must establish a solid set of procedures and technologies that combine user rights and control over what data is disclosed to both comply with privacy standards and reduce the risk of a data breach.

Create a Data Classification System

The process of classifying sensitive data is the act of determining the categories of information that a company receives and selecting how it is stored and used by its employees. Data is classified into one of the following groups: 

  • Structured data is data that is well-structured and can be read by machine learning algorithms. 
  • Unstructured data is qualitative information that cannot be easily absorbed and assessed using normal data procedures. 

Data categorization enables companies to identify the content and context of data that they use and maintain. A company may make better judgments about what to do with and how to protect its data as a consequence of data classification. 

There are several methods for categorizing data. One example is the use of regular expressions (also known as regexes) by data discovery systems with classification capabilities. Heuristics may be used by other programs to examine data context. 

When the data discovery process is complete, the cloud DLP system will classify data based on predefined categories such as “important,” “confidential,” or “sensitive.” Administrators may now locate and analyze batches of data and prioritize preserving information based on these categories.

IAM Controls

Identity and access management is the process of creating and managing users, groups, and access for persons inside a corporation (IAM). IAM employs both tools and rules to guarantee that the proper persons have access to the relevant resources at the appropriate times and for acceptable reasons. Basic IAM procedures follow the principle of least privilege, which asserts that only explicit administrative instructions should be used to increase a user’s or component’s access level. The concept of least privilege is an essential step in reducing the risk of a data breach.

Systems administrators may use IAM to control what third parties have access to structured and unstructured data.  Organizations cannot fully mitigate the risk of a security breach of personal information by using information security technologies. Employees working on their own accord pose a substantial threat that must be managed with IAM practices and policies.

The process of IAM begins with employee identification. The use of a centralized system makes the process easier. Employees should be assigned to groups, which are then given access to resources and information as authorized (i.e., as per their group memberships). 

Administrators must combine several tools and rules to effectively implement a centralized access policy. A managed service provider can protect organizations by implementing an enterprise service bus that leverages many systems and processes to facilitate efficient authentication, authorization, and auditing (IAM).

The Takeaway

Cloud computing services are designed to run many different applications and processes to scale efficiently. Each cloud service provider has a data protection system that follows best practice security measures. Organizations cannot be certain of the effectiveness of those measures. Therefore, they must employ cloud DLP technologies and IAM procedures to protect data stored in third-party clouds, which may or may not have prioritized security concerns. If you enjoyed this article, check out our blog for more security tips.

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