Imperva DSF Secures Your Data in Amazon Web Services Enterprise Data Lakes

Data lakes serve as a central repository for storing several data types – structured, semi-structured, and unstructured – at scale. One of the ways data lakes are useful is they do not require any upfront work on the data. You can simply integrate and store data as it streams in from multiple sources.

Amazon’s AWS data lakes are some of the most popular cloud data solutions available on the market today. AWS data lakes are purpose-built to deliver secure cloud architectures to customers. AWS helps relieve its customers’ operational burden by operating, managing, and controlling the components from the host operating system and virtualization layer down to the physical security of the facilities in which the service operates. It is the customer’s responsibility, however, to secure their sensitive data. You can see how this works in the shared responsibility model AWS follows.

Risks to sensitive data start to pick up momentum when organizations move workloads to the cloud quickly and lose track of where their sensitive data resides. To maintain security in these environments, you need a good data catalog, know where data copies are, where snapshots may be, etc. You must also have enforceable access control policies in place around sensitive data. You must have audit trails, the ability to run data through forensics if needed, the ability to validate what entitlements are and reduce them, and the capacity to check for vulnerabilities from a surface area perspective. These aren’t new practices; they have been integral to how organizations have applied data-centric security strategies to data repositories for years. What’s new is the need to apply these practices to cloud-managed environments like AWS data lakes.

Imperva Data Security Fabric (DSF) enables enterprises to protect their sensitive data in AWS enterprise data lakes and help demonstrate data compliance. The Imperva DSF solution enables AWS customers to see and secure their sensitive data through a single comprehensive platform and leverage a unified security model across Amazon Aurora, Amazon Redshift, Amazon Relational Database Service (RDS), Amazon DynamoDB, Amazon Athena, and AWS CloudFormation without…