Lack of guidelines
Unaware of my unknowns. What rules should the security team establish?
Detect data threats before they become security incidents or breaches
Protecting sensitive data is challenging for enterprise security groups with limited resources and tools. Often it is the group's tools themselves that make data breach detection so difficult. Tools that cannot correctly contextualize alerts overwhelm security staff with an avalanche of mostly "false positives" making it very hard to know what to do or even where to begin. Organizations need advanced data risk analytics to eliminate all the noise and help security staff gain actionable threat insights to accelerate risk mitigation and breach detection.
Top data security guidelines
Investigating data threats through the information that a typical UEBA solution (such as a SIEM) provides often requires pre-knowledge of the accessed data set or deep knowledge of data access languages like Structured Query Language (SQL) to know if any sensitive data has been misused or if users are accessing data inappropriately.
Data prioritization
Unsure which data to monitor/audit. What data should the security team monitor?
Unintelligible data
SQL isn't the security team's forte. How does the security team interpret data activity events?
Too much data
Overwhelmed by system data flows. How does the security team handle so many data events?
Data security, unleashed
Imperva Data Risk Analytics elevates the security and compliance capabilities of IT and security staff by providing automation, filtering, and insights & actions in plain language that accelerate customers' paths to data security confidence.
Imperva Data Risk Analytics
Do more with less
Imperva Data Risk Analytics (DRA) identifies abnormal user behavior that can lead to bad practices, hostile intrusions, and data compromise. Imperva DRA translates complex technical events into plain language that IT operations teams and security staff members can immediately understand. Imperva DRA provides an intuitive dashboard that provides a prioritized incident summary of questionable events that anyone can click through, which in turn provides a complete description of the threat with actionable intelligence for remediation.
- Purpose-built analytics using machine learning to detect suspicious data activities
- Prioritize and group high-risk incidents to elevate team skills via machine learning
- Interprets data store events and provides actionable insights to accelerate remediation
- Reduces the count of events to investigate for efficiency and speed
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Prioritize and group high-risk incidents to elevate team skills
Imperva Data Risk Analytics (DRA) prioritizes critical incidents by applying grouping and scoring algorithms that factor in variables such as sensitive data type, privileged account, amount of data involved, and more. Suppose multiple incidents are related (e.g., all associated with the same user account, or multiple users are abusing the same service account). In that case, Imperva DRA groups the incidents into one issue, prominently showing security staff the high-risk incident and suppressing false positive noise.
- No configuration needed
Unsupervised learning transforms raw activity data into valuable information – without the need for a DBA - Fully automated
Events are prioritized based on best practices defined using pre-built or custom models – without the need for a data scientist - Unique triangulation
Insights based upon the synthesis of user behaviors, application & API access patterns, and data source context
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Our model has been trained on petabytes of data, with algorithms refined over more than a decade
With Imperva Data Risk Analytics and ServiceNow, you can avoid burning out your cyber security employees
In today's world, CIOs and CISOs face a harsh reality regarding the security staff shortage. With the deflating economy, nationalism, cybercrime, and nation-led adversaries, the demand for security personnel has increased, making it challenging for organizations to find and retain skilled security staff.
Customers are also looking for solutions to offload tasks from their security staff, and this is where Imperva DSF Data Risk Analytics (DRA) comes in. With Imperva DSF DRA, most cases related to bad practices and insider threats can be handled and resolved by other non-security teams in the organization. Imperva DSF DRA, when integrated with ServiceNow, can automatically triage data risk incidents to different members or groups like data experts, access experts, direct managers, and database owners who can receive and resolve incidents directly and immediately without expensive human intervention, freeing security specialists to work on high stake data risk issues.
We needed a data security platform that offers more than native scanning and audit logs of our databases. Imperva Data Security Fabric provides not only the essential monitoring and blocking capabilities, but also consolidates data risk insights to prevent potential threats across all of our databases.
Naoki Nishida Senior Manager Head of Operations Group
Data Risk Analytics in two minutes
Imperva Data Risk Analytics (DRA) protects enterprise data stored in enterprise databases and file shares from theft and loss caused by compromised, careless or malicious users. By dynamically learning users' standard data access patterns and then identifying inappropriate or abusive access activity, DRA proactively alerts IT teams to dangerous behavior.
