Why Your Organization Needs Data-centric Security

Digital Transformation has amplified the significance of data, now hailed as the world's most valuable commodity. Unlike oil, data's intrinsic value is not uniform and can become worthless or even hazardous if mishandled. The growing incidents of data breaches highlight the inefficacy of current data protection measures. As organizations navigate complex regulatory frameworks like GDPR, the cost of data breaches—averaging over $4M—extends beyond financial losses to reputational damage. The persistence of data breaches despite advanced security technologies signifies a critical flaw: treating data protection as a one-time event rather than a continuous process. This realization underscores the need for data-centric security, where data remains protected throughout its lifecycle, irrespective of location or transformations. Since data seldom resides in a single database, layered security controls and centralized policy management are paramount.

Modern organizations utilize diverse databases and storage solutions, complicating security due to disparate and often incompatible security controls. Internal security features, though essential, fall short as they lack business context and cannot provide comprehensive protection alone. Unified data-centric security extends beyond database security to incorporate continuous monitoring, access management, compliance auditing, and more. This comprehensive approach integrates multiple technologies, from data discovery to advanced threat detection, and mandates centralized coordination to ensure coverage and mitigate risks.

Imperva exemplifies this data-centric philosophy with its Data Security Fabric. By providing enterprise-wide visibility, rigorous data discovery, access management, continuous compliance auditing, and proactive breach prevention, Imperva aligns with the layered security model. Their solutions automate and streamline data protection and compliance processes, integrating seamlessly with other enterprise tools. Despite the intricacies of data protection, Imperva's unified approach offers a blueprint for safeguarding data across diverse environments.

• The average cost of a data breach exceeds $4M.
• The GDPR and California's Privacy Rights Act enforce heavy penalties for mishandling customer data.
• Most modern databases come with integrated security controls such as encryption and activity audits.
• NoSQL database misconfigurations once led to a breach affecting over 28,000 databases, resulting in ransom demands.
• AWS provides over 15 different database engines, each with distinct security controls.
• Some database security features, like full disk encryption, are often misinterpreted as comprehensive solutions.
• Cloud service providers cannot be held legally responsible for data breaches under the shared responsibility model.
• Physical, technical, and administrative control layers adhere to the "defense in depth" security principle.
• Imperva's unified security approach utilizes their Data Security Fabric to protect data across various environments.
• Imperva's advanced analytics engine detects policy-violating and evasive exploit behaviors.

• "Data can be anything from 'the new gold' to 'the new garbage' or even a dangerous kind of 'digital poison.'"
• "Security only works when it is always on."
• "Data protection should always be treated as a continuous process, not a one-time event."
• "Data cannot always reside in a single database; it is constantly moving between different storage, processing, and visualization platforms."
• "The layered security approach ensures that every bit of telemetry is useful and directly contributes to a quick response to every incident."
• "Imperva's motto: 'Protecting data and all paths to it.'"
• "Imperva uses an advanced, purpose-built analytics engine to recognize signs of potential account compromise or malicious insider behavior."
• "The shared responsibility model clearly places full responsibility for their data on cloud customers."
• "No organization has ever managed to keep all of its data in a single database; they end up using a variety of engines and storage solutions."
• "Technologies like machine learning can provide not just real-time correlation of security telemetry but intelligent decision support."