A framework for success: Tackling the challenges of multicloud security
The growing necessity of multicloud security
As enterprises increasingly adopt multicloud strategies to optimize operations, managing data security across different cloud environments becomes more complex and critical. The benefits are clear, but so are the risks. Effective protection of multicloud data estates demands identifying and managing sensitive data, overcoming blind spots, and applying consistent security controls. This guide offers an all-encompassing framework to tackle these challenges, so that organizations can secure their multicloud environments effectively.
For an in-depth guide on tackling multicloud data security challenges, download our full PDF.
Dive into our thinking:
Prioritizing Data Security
To effectively secure multicloud environments, organizations must:
- Understand Their Data: Identify where sensitive data resides across environments.
- Apply Consistent Security Controls: Implement encryption, access restrictions, and other control measures uniformly.
- Enforce Governance: Ensure ongoing regulatory compliance and manage data life cycles effectively.
- Prevent Data Loss: Detect and prevent accidental oversharing using integrated policies and controls.
Discover the Power of a Multicloud Data Estate
A multicloud data estate refers to managing an organization's data across multiple cloud environments.
Here are some key considerations:
- Alignment: Engage with data governance, legal, compliance, privacy, and business teams to streamline decision-making processes.
- Platform Management: Minimize the number of technologies and platforms used to manage data.
- Strategic Risk Management: Identify and mitigate key risks such as lack of visibility, misconfigurations, data leakage, insider threats, unauthorized access, and compliance issues.
A Multicloud Data Governance Framework
Implementing robust data governance can help mitigate common risks:
- Know Your Data: Conduct scans to identify and classify important data across the cloud environment.
- Protect Your Data: Use flexible security measures like encryption and access controls that persist even when data moves across platforms.
- Prevent Data Loss: Monitor high-risk user activity and enforce data loss prevention policies.
- Govern Your Data: Use centralized data management for retention, deletion, and compliance.
Case Studies
Case Study 1: Sensitive Data Exfiltration from an AWS S3 Bucket
A data engineer accidentally made an AWS S3 bucket public, resulting in a breach. The solution involved:
- Using Purview: For scans, classification, and applying sensitivity labels.
- Enhanced Risk Indicators: To detect and alert high-risk misconfigurations.
- Persistent Labels: To protect data even after being mistakenly shared.
Case Study 2: Sensitive Data Leakage from Azure SQL to Power BI
A banking company exposed sensitive financial data due to lack of persistent security controls. The solution involved:
- Using Purview: For data discovery, classification, and applying sensitivity labels to SQL databases and Power BI dashboards.
- Real-Time Alerts: DLP policies to notify on the detection of sensitive data in dashboards.
- Ongoing Governance: Regular reviews and secure management of data through unified platforms.
Connect with Us
To learn more about securing your multicloud data estate, or for personalized assistance, contact our experts:
- Raman Kalyan
- Michael D. Gomez
- Daniel Hidalgo
- Jim Wilhelm
- Ravi Kiran Poluri
- Venoth Lal
- Annapurna Saripalli
- Ryan McGurgan
- Pankaj Parikh
Insights on cyber security
KPMG professionals are passionate and objective about cyber security. We’re always thinking, sharing and debating. Because when it comes to cyber security, we’re in it together.
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