Database Security

Imperva Database Firewall (DBFW) “strongly” reduces the risk of security breaches of an organization's confidential data against all possible sources of threat. Dishonest employees: DBFW monitors, controls and precisely accounts for user access to databases. Dishonest administrators: DBFW precisely manages privileged user access and privileges. Cyber criminals: DBFW blocks database attacks and data manipulation attempts. Imperva Data Security Fabric (DSF) - a collection of technologies that together create a complete Data Security solution for organizations of all sizes. Imperva Data Risk Analytics (DRA) - protects data stored in corporate databases from theft and loss caused by compromised, careless or malicious users.
Database Security
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Imperva Database Activity Monitoring (DAM) / Database Firewall (DBF)

This is part of the DSF platform but can also operate as a standalone product. The solution consists of agents, agent gateways (previously known as DAM/DBF Gateway), and managing components MX/SOM. The Imperva DAM/DBF solution secures sensitive data stored in databases, providing full visibility into data usage, vulnerabilities, and access rights. It allows security, audit, and risk specialists to improve data security and meet compliance requirements.

Imperva Data Security Fabric (DSF)

This is a collection of technologies that together create a Data Security solution for organizations of any size. Data Security Fabric includes, among others, classic Data Activity Monitoring (DAM) components that rely on agent-based audit data collection, as well as agentless mechanisms that utilize native auditing present in nearly all production databases. Additionally, DSF includes analytical tools and a range of other features that help implement comprehensive projects for monitoring and protecting enterprise data assets. DSF extends beyond structured data (stored in relational/structured databases) and provides the ability to extend protection to unstructured data. Imperva DSF provides proactive control and predictive analytics, enabling security analysts and management personnel to leverage monitoring capabilities, security assessment, risk modeling, and attack detection to avoid harmful data breaches or non-compliance. For example, Imperva DSF identifies behaviors that violate data usage policies, and advanced risk analysis detects indicators of malicious insider activity or compromised user accounts that may bypass data repository access controls and circumvent data encryption.

Imperva Data Risk Analytics (DRA)

Protects data stored in corporate databases from theft and loss caused by compromised, careless, or malicious users. By dynamically learning normal user data access patterns and then identifying inappropriate or improper access actions, Data Risk Analytics proactively alerts IT teams to dangerous behaviors.