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Data Loss Prevention: 7 Best Practices for SAP Security

By David Vincent • August 20, 2021

A constantly evolving threat landscape and compliance environment with inconsistent standards have made data loss prevention (DLP) a vital component of an organization’s SAP data security strategy. The global cost of data breaches hit a record-high in 2021 ($4.2 million per incident), highlighting the importance of a robust DLP strategy to protect organizations from financial, legal, and reputational damages. 

What Is Data Loss Prevention?

Data Loss Prevention is the practice of identifying and preventing data breaches, exfiltration, or unwanted loss or destruction of sensitive data. Businesses use DLP solutions for SAP and PeopleSoft applications mainly to:

  • Secure Personally Identifiable Information (PII)
  • Comply with data security and privacy regulations
  • Protect intellectual property critical to the organization
  • Prevent unauthorized transfer of data outside the organization

Seven Data Loss Prevention Best Practices

For any DLP strategy, you need to understand which organizational data to secure, where that data resides, who has access to that data (and when), and how the data should be used. Unfortunately, data loss is difficult to spot because data routinely moves in and out of an enterprise and closely resembles normal traffic. Let’s take a look at a list of data loss prevention best practices that have helped our customers achieve their data security goals and meet compliance standards.

  1. Configure Dynamic Data Loss Prevention Policies
    Preventing unauthorized exposure of sensitive information and protecting against insider data leakage begins by configuring contextual, attribute-based DLP policies that restrict transactions based on user and data attributes. Unfortunately, traditional role-based access controls (RBAC) can’t completely safeguard data in dynamic environments as static roles fail to leverage contextual attributes such as time of the day, geolocations, IP address, transaction type, etc.   
  1. Establish Clearly Defined Rulesets for Segregation of Duties
    Establishing a clearly defined ruleset for segregation of duties that divides business processes between multiple users helps limit the risk of fraud and error while ensuring that a user’s access privileges do not conflict or violate business policies.
  1. Deploy Policy-Based Data Masking and Redaction
    Companies can enable dynamic data masking to reduce unnecessary exposure of sensitive information while allowing employees to do their jobs. For example, masking specific fields on a page an employee is accessing. Or using click-to-view masking to unmask data or require an MFA challenge before data is revealed to log access to a particular field. And don’t forget to protect non-production environments where dynamic data masking ensures development or testing teams can only access the data they need and nothing more.
  1. Continuously Monitor Data Access And Usage
    Monitoring user behavior around data access and usage in real-time at a granular level provides visibility into how users interact with sensitive data, triggering security event alerts for high-risk access and abnormal activity at the field level. (Native application logging capabilities cannot tell the difference between malicious user activity and normal usage.)
  1. Increase The Levels Of Access Control & Monitoring for High-Privilege Users
    Because privileged user accounts are magnets for hackers, companies should isolate activity and access data by these accounts to ensure integrity and alignment with current business policies. For example, an employee from the HR department needs access to payroll information to do their job, but do they need that access outside of office hours or from an unknown IP address? 
  1. Closely Monitor Report and Query Downloads
    Monitor instances of query running and download attempts, ensuring that sensitive queries are not being downloaded onto unauthorized devices, from suspicious locations, or outside business hours.
  1. Leverage DLP Solutions to Automate As Much As Possible
    For all the features and value ERP systems provide, they lack the functionality to provide a dynamic, automated data loss prevention solution. Automating DLP processes across the organization allows you to enforce dynamic policies to identify and protect data before it exits the organization. In addition, automating compliance audits allows you to constantly monitor data access and usage and alert security teams to abnormal activities. 

How Appsian Security Helps Enable Your SAP Data Loss Prevention Strategy

Whether careless or malicious, employee, partner, or contractor, it can be difficult to tell the difference between a user’s regular activity and activity intent on causing harm or theft. The Appsian Security Platform (ASP) helps SAP customers deploy these data loss prevention best practices, and many more, to prevent unauthorized exposure and exfiltration of sensitive data, PII, and intellectual property.

By configuring dynamic access controls, you can uniformly enforce policies that restrict transactions based on user and data attributes. In addition, you can deploy policy-based data masking that help you comply with data security and privacy regulations by reducing the exposure of high-risk data.

Contact us today for a demonstration and see for yourself how Appsian Security can help with your data loss prevention strategy.

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