Data Governance and Protection in the Cloud: Leveraging AWS Tools for Enhanced Security

The world’s most valuable resource is data. After cloud revolution, ensuring data security, compliance and responsible use, became even more critical. Data governance is a set of strategies and rules that aims to guarantee quality integrity and security of data from when they are generated and throughout their entire lifecycle, preventing inadvertent issues or data loss. Data governance defines who can take which actions, on which data, in which situations, and using which methods.
This article aims to explore best practices to address risks associated with the cloud using services provided by AWS to ensure data protection and to help mitigate risks around company’s sensitive data.

What is data?

First, let’s think about what data has become to be today. Data is becoming core to business success. In fact, every business including finance, retail, medical, is a data business. Data is absolutely essential for ensuring your business is successful.
The growth of data is becoming the standard, and enterprise data is expected to triple by 2025, with 87% of that data predicted to be stored in the cloud.
The explosion of data is a challenge. The nature of the digital economy increases risk because data is shared with users, organizations, and customers. So, with that, let’s look at data governance.

Data Governance

In today’s digital age, data governance and protection are paramount, especially within the realm of cloud computing. Ensuring that data is managed securely and efficiently is crucial for maintaining trust and compliance.
Data governance is a data management concept that enables organizations to ensure high data quality and it is used to securely support business objectives. This is done by defining policies and adding controls to manage risk.
The amount of data being generated creates a balancing act between access and control.

There is a fine line between the ability to use that data and the ability to extract business value out of those data. It is important to ensure that usage is correct and in accordance with organizations policies.

So, what this boils down to is that the trust in data is mutual. It is about businesses being able to trust their data and external parties trusting businesses with their data.
To ensure trust is built, data protection and governance are becoming more and more critical every day. Now, let’s look at security and controls briefly.

Security and Controls

With governance, where we looked at things in hierarchy, for security let’s look at it in layers.

AWS Multi layer security, source [1]

AWS offers a full suite of security features to ensure your data is secure against bad actors, whether external or internal to your organization.

• IAM policy: allows you to grant and restrict access to your users.
• Multi-factor authentication: makes it difficult for someone to gain an access by stealing your username and password.
• Immutable backup: protect your data against any modification or deletions.
• Encryption schemes: offered through Key Management Systems (KMS) and integration with other AWS services.
• Physical security and digital separation of user roles
• Audit tracking capabilities: to track who is accessing what data

Data Governance risks in the Cloud

Cloud environments, while offering numerous benefits, also introduce specific security risks. Understanding these risks and employing the right tools to mitigate them is essential for safeguarding sensitive information.
Risks associated with data governance in the cloud cover a broad range of concerns, including:

• Data Breaches and Unauthorized Access: Cloud environments introduce new potential points of attack, making it crucial to implement strong access controls and data security measures to prevent unauthorized access to sensitive information.
• Data Loss and Corruption: Risks such as accidental deletion, hardware malfunctions, or malware attacks can result in data loss, highlighting the need for effective data backup and recovery strategies.
• Non-compliance with Regulations: Organizations must adhere to various industry-specific regulations based on their geographic location and the types of data they manage. Non-compliance can lead to substantial financial penalties and damage to reputation.
• Shadow IT and Unauthorized Data Storage: Employees may bypass established data governance policies by utilizing unauthorized cloud services, which introduces security risks and reduces visibility over data management.
• Lack of Data Visibility and Control: Challenges in monitoring data movement and usage within the cloud can impede effective data governance and compliance efforts.

These potential risks underscore the necessity of implementing comprehensive data governance strategies and utilizing robust security solutions to protect sensitive data in the cloud.

Creating a Strong Data Governance Framework

The cornerstone of secure and compliant management of cloud data is the creation of a well-defined data governance framework. Here are essential elements to consider:

1. Develop a Comprehensive Data Governance Strategy:

Data Classification: Establish a clear system for classifying data that identifies the sensitivity and potential impact of data if compromised. This approach enables focused protective measures and aids in regulatory compliance.

Data Ownership: Explicitly assign roles and responsibilities for data ownership across various departments and user groups. Data owners are primarily accountable for ensuring that data is secure, properly managed, and utilized in accordance with established guidelines.

Data Access Controls: Apply detailed access controls based on the least privilege principle. This limits users to access levels that are strictly necessary for their job functions, thereby reducing the risk of unauthorized access to sensitive data.

Data Retention: Set forth data retention policies that specify the duration for storing different types of data and outline procedures for archiving or deleting data. This not only helps in adhering to legal and regulatory mandates but also reduces costs associated with unnecessary data storage.

2. Promote a Culture of Data Security Awareness:

Education: Inform your employees about the best practices in data governance and the critical nature of handling data responsibly. Regular training sessions can provide them with the skills needed to recognize and address data security threats.

Communication: Encourage a culture where open communication about data security issues is standard practice, and potential security incidents are reported immediately. Prompt reporting allows for quick action, helping to minimize any potential harm.

AWS Security Services for Data Governance and Protection

AWS offers a range of services that can significantly improve your data security posture in the cloud:

AWS Identity and Access Management (IAM): This foundational service enables detailed access control by creating users, groups, and policies that specify permissions for accessing resources and under specific conditions.

AWS Key Management Service (KMS): KMS facilitates the secure storage and management of encryption keys that are used to safeguard data at rest and in transit, ensuring that only authorized personnel can access sensitive information.

AWS CloudTrail: CloudTrail provides ongoing monitoring and logging of user activities and API usage within your AWS environment, aiding in audits, investigations, and the detection of potential security threats.

AWS Security Hub: This service provides a unified overview of your security status across various AWS services. It compiles data from multiple security tools, streamlines the prioritization of remediation actions, and offers insights into potential security vulnerabilities.

Additionally, you might consider exploring:

Amazon Inspector: This service automates security assessments of your AWS resources, identifying possible vulnerabilities, configuration errors or deviations from best practices. After performing an assessment, Amazon Inspector produces a detailed list of security findings prioritized by level of severity. These findings can be reviewed directly or integrated with other AWS services like Amazon CloudWatch Events, which can trigger automated remediation actions based on specific criteria.

Key Features:

• Automated Assessments: Runs security vulnerability assessments automatically to check for exposures, vulnerabilities, and deviations from best practices.
• Rich Set of Rules: Leverages a library of hundreds of built-in rules to identify security vulnerabilities and issues related to application security, network security, OS vulnerabilities, and more.
• Integration and Automation: Easily integrates with other AWS services and can trigger automated remediation actions based on its findings.

Amazon Macie: It is a fully managed data security and data privacy service that uses machine learning and pattern matching to detects and classifies sensitive data stored in S3 buckets, assisting organizations in complying with regulations and reducing data security risks. Macie is particularly useful for identifying and securing Personally Identifiable Information (PII) or intellectual property, and it provides dashboards and alerts that help you understand how this data is being accessed or moved. The service continuously monitors data access activity for anomalies, and generates detailed alerts when it detects risk of unauthorized access or data leaks. Amazon Macie is something that becomes increasingly challenging as data volumes grow.

Key Features:

• Data Discovery and Classification: Automatically discovers and classifies sensitive data in AWS S3 buckets using machine learning and pattern matching.
• Continuous Monitoring: Continuously monitors data access patterns and evaluates them for suspicious activity using anomaly detection techniques.
• Alerts and Dashboards: Provides an intuitive dashboard for visualizing data storage, access patterns, and alerts for governance and compliance.

Amazon GuardDuty: It is a threat detection service that continuously monitors for malicious or unauthorized behavior to help protect your AWS accounts and workloads. It uses machine learning, anomaly detection, and integrated threat intelligence to identify and prioritize potential threats. GuardDuty analyses billions of events across multiple AWS data sources, such as AWS CloudTrail, Amazon VPC Flow Logs, and DNS logs.

Key Features:

• Intelligent Threat Detection: Utilizes machine learning and anomaly detection to identify threats more accurately.
• Integrated Threat Intelligence: Uses threat intelligence feeds to identify known malicious sources and activities.
• Seamless Integration: Easy to enable without the need for additional security software or infrastructure. It integrates with AWS management tools and can automate responses using AWS Lambda.

AWS Audit Manager continuously audits AWS usage to simplify how organizations assess risk and compliance with regulatory standards. AWS Audit Manager automates evidence collection and enables audit capability in the cloud to scale as needed. AWS Audit Manager makes it easy for companies to assess whether their policies, procedures, and activities are operating effectively.

AWS Config provides the means to assess, audit, and evaluate AWS resource configurations. AWS Config continuously monitors and records those configurations, automating the evaluation of recorded configurations against desired configurations. With AWS Config, organizations can review changes in configurations and relationships between AWS resources, dive into detailed resource configuration histories, and determine overall compliance against internal guidelines, simplifying compliance auditing, security analysis, change management, and operational troubleshooting.

Implementing Data Encryption for Enhanced Security

Data Encryption at Rest: Encrypt data stored in S3 buckets and other storage services using KMS. Choose the appropriate encryption method based on your specific needs:

• Server-side Encryption with KMS (SSE-KMS): AWS manages the encryption key, offering simplicity and scalability.
• Customer-managed Encryption Keys (CMKs): You manage your own encryption keys, providing increased control and customization.

Data Encryption in Transit: Encrypt data during transfer between AWS services or to on-premises environments. Utilize services like:

• HTTPS: Encrypts communication between web browser and web server, protecting data in transit.

Conclusion

Addressing data governance risks in the cloud necessitates a thorough and multi-faceted strategy. By implementing a strong data governance framework, promoting a culture of data security awareness, and utilizing the wide array of security services and tools provided by AWS, organizations can guarantee the secure, compliant, and responsible management of data within their cloud infrastructure.

References

• [1] AWS Summit ASEAN 2022 — Data governance and protection Strategies with aws. https://www.youtube.com/watch?v=GsoHw5V9tFM
• [2] Mitigating Data Governance Risks in the Cloud: Best Practices for Secure and Compliant AWS Data Management. https://www.linkedin.com/pulse/mitigating-data-governance-risks-cloud-best-practices-kaira-bedi-hzxuf/
• [3] Cloud Governance: Driving Success and Security in the Cloud. https://pages.awscloud.com/rs/112-TZM-766/images/AWS_CloudGovernance_ebook_Driving-Success-and-Security-in-the-Cloud.pdf