Setting Up Secure Data Lakes for Starlight Financial: A Guide to AWS Implementation

Continuing on our fictitious financial company, Starlight, series of posts, here is how to set up a data lake on AWS with security as the primary thought.

Introduction

In the fast-moving financial industry, data is a core asset. Starlight Financial needs to use vast amounts of data for decision-making, improving customer experience, and keeping ahead of its rivals. Consider a data lake: it's a vital part of modern data architectures, letting enterprises store both structured and unstructured data in large quantities of any kind whatsoever. Tony Hoare famously observed that with great data comes great responsibility — and so it is. Eventually, it will be some comfort to know that one of the most important steps for consultancy in validating big data architectures using AWS services has been elucidated. That is to say: test them just like any other system you might use. This is a guide to establishing a highly secure data lake using AWS services, specifically focused on the needs of financial institutions, written by us using a blog structure.

Overview of AWS Services for Secure Data Lakes

AWS offers a comprehensive suite of services that can be leveraged to build and secure data lakes. Key services include:

Amazon S3 (Simple Storage Service)

Role

Amazon S3 serves as the primary storage layer for your data lake, offering highly scalable, reliable, and low-latency data storage.

Scalability

S3 can store virtually unlimited amounts of data, making it ideal for data lakes that need to handle large volumes of structured and unstructured data.

Durability and Availability

S3 is designed for 99.999999999% (11 nines) durability and offers high availability, ensuring that data is always accessible.

Security Features

• Access Control: S3 provides multiple mechanisms for access control, including bucket policies, access control lists (ACLs), and IAM policies.
• Encryption: Supports server-side encryption (SSE) with Amazon S3-managed keys (SSE-S3), AWS KMS-managed keys (SSE-KMS), and customer-provided keys (SSE-C).
• Logging and monitoring: S3 access logs and AWS CloudTrail can be used to monitor access and changes to data.

AWS Lake Formation

Role

AWS Lake Formation streamlines the process of building, securing, and managing a data lake.

Data Ingestion

AWS Lake Formation simplifies the ingestion of data from various sources, including databases and streaming data, into your data lake.

Data Cataloging

AWS Lake Formation automatically catalogs data, making it searchable and easy to manage. This is crucial for organizing large datasets.

Security and Access Control

• Fine-grained permissions: Allows for fine-grained access control at the database, table, and column levels, ensuring that sensitive data is protected
• Unified security model: Integrates with IAM and AWS KMS to provide a unified security model across your data lake.

AWS Identity and Access Management (IAM)

Role

IAM is essential for managing access to AWS resources, ensuring that only authorized users and applications can access your data lake.

User and Role Management

IAM allows the creation of users, groups, and roles with specific permissions, facilitating the implementation of role-based access control (RBAC).

Policy Management

IAM supports the creation of detailed policies to define who can access what resources and under what conditions.

Security Features

• Multi-Factor Authentication (MFA): Enhances security by requiring a second form of authentication
• Federated access: Supports federated access using SAML or OpenID Connect, allowing integration with existing identity providers

AWS Key Management Service (KMS)

Role

AWS KMS provides centralized control over the cryptographic keys used to protect your data.

Key Management

AWS KMS simplifies the creation, management, and rotation of encryption keys, ensuring that data is encrypted at rest.

Integration With AWS Services

AWS KMS seamlessly integrates with services like S3, RDS, and EBS, allowing for easy encryption of data.

Security and Compliance

• Audit logs: Provides detailed logs of key usage through AWS CloudTrail, aiding in compliance and auditing efforts
• Custom key stores: Supports custom key stores backed by AWS CloudHSM, providing additional control over key management

AWS CloudTrail and AWS Config

Role

These services provide monitoring and compliance capabilities, ensuring that your data lake environment is secure and compliant with regulations.

AWS CloudTrail

• API activity logging: Records all API calls made within your AWS account, providing a comprehensive audit trail of user activity
• Security analysis: Helps in detecting unusual activity and potential security threats by analyzing logs
• Integration with SIEM tools: Can be integrated with Security Information and Event Management (SIEM) tools for enhanced security monitoring

AWS Config

• Resource inventory: Maintains a comprehensive inventory of AWS resources and their configurations
• Compliance auditing: Continuously monitors and records AWS resource configurations and compares them against desired configurations
• Change management: Alerts you to changes in resource configurations, helping to identify and address potential security issues
• Amazon S3: The backbone of your data lake, providing scalable storage
• AWS Lake Formation: Simplifies the process of setting up a secure data lake
• AWS Identity and Access Management (IAM): Manages access to AWS resources
• AWS Key Management Service (KMS): Provides encryption for data at rest
• AWS CloudTrail and AWS Config: Enable monitoring and compliance

Step-by-Step Guide to Setting Up Security Measures

Step 1: Setting Up Amazon S3 Buckets

Begin by creating an S3 bucket to store your data. Ensure that you enable versioning and server-side encryption.

aws s3api create-bucket --bucket starlight-financial-datalake --region us-east-1

aws s3api put-bucket-versioning --bucket starlight-financial-datalake --versioning-configuration Status=Enabled

aws s3api put-bucket-encryption --bucket starlight-financial-datalake --server-side-encryption-configuration '{
  "Rules": [{
    "ApplyServerSideEncryptionByDefault": {
      "SSEAlgorithm": "AES256"
    }
  }]
}'

Step 2: Configuring AWS Lake Formation

AWS Lake Formation simplifies the process of setting up a secure data lake. Start by registering your S3 bucket.

aws lakeformation register-resource --resource-arn arn:aws:s3:::starlight-financial-datalake --use-service-linked-role

Step 3: Implementing Access Controls With IAM

Define IAM policies to control access to your data lake. Ensure that only authorized users and applications have access.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "s3:*",
      "Resource": "arn:aws:s3:::starlight-financial-datalake/*",
      "Condition": {
        "IpAddress": {"aws:SourceIp": "192.0.2.0/24"}
      }
    }
  ]
}

Step 4: Encrypting Data With AWS KMS

Use AWS KMS to encrypt data at rest. Create a KMS key and apply it to your S3 bucket.

aws kms create-key --description "KMS key for Starlight Financial data lake"

aws s3api put-bucket-encryption --bucket starlight-financial-datalake --server-side-encryption-configuration '{
  "Rules": [{
    "ApplyServerSideEncryptionByDefault": {
      "SSEAlgorithm": "aws:kms",
      "KMSMasterKeyID": "arn:aws:kms:us-east-1:123456789012:key/abcd1234-a123-456a-a12b-a123b4cd56ef"
    }
  }]
}'

Step 5: Monitoring and Compliance With CloudTrail and AWS Config

Enable AWS CloudTrail and AWS Config to monitor access and changes to your data lake.

aws cloudtrail create-trail --name starlight-financial-trail --s3-bucket-name starlight-financial-logs

aws configservice put-configuration-recorder --configuration-recorder '{
  "name": "default",
  "roleARN": "arn:aws:iam::123456789012:role/config-role"
}'

Best Practices to Enhance Data Security

1. Purpose of Data Classification

The purpose of data classification is the sensitivity and importance of different data types that help to apply appropriate security measures.

• Data classification development: Classification of data based on sensitivity (public, internal, confidential, and restricted)
• Automation classifications: Use tools (like AWS Macie) that can also automatically discover, classify, and protect sensitive data stored in AWS.
• Continuous updates: Continue to update classifications as new data is ingested and the business needs change.

2. Purpose of Least Privilege

The purpose of least privilege is to reduce the risk of unauthorized access by limiting users to tasks that they must do.

• Use IAM Policies: Create fine-grained IAM policies that limit user access to specific resources and actions.
• Role-Based Access Control: Use RBAC to assign privileges according to the role instead of the user.
• Regular Review: Periodically review and adjust permissions to ensure they are in line with job responsibilities.

3. The Purpose of Regular Audits

Systematically inspect to detect and remedy security problems.

• Security audits: Carry out regular security reviews to test how well the controls are holding up against threats and potential sources of failure.
• Vulnerability assessments: Use tools like AWS Inspector to automate security checks and find weak points in your AWS environment.
• Compliance checks: Make sure you keep up with industry standards and regulations such as GDPR, PCI-DSS, and SOX.

4. The Purpose of Data Masking

The purpose of data masking is to hide sensitive data and to protect it from prying eyes.

• Dynamic data masking: Using dynamic data masking, sensitive information is concealed in real-time on the basis of who is doing the asking
• Tokenization: Replacing sensitive data with tokens, so it's not exposed to risk anymore
• Encryption on the move, data in Stock: Ensure all data is encrypted whether moving about or at rest using AWS KMS and SSL/TLS protocols.

5. Automated Backup

Eliminate unrecoverable data loss and ensure proper data availability with regular backups.

• Versioning: Use S3 versioning to keep track of multiple versions of an object, even if it is deleted inadvertently.
• Automated backup solutions: Your AWS Backup strategy includes scheduled backups for your data lake.
• DRP (Disaster Recovery Plan) Test: Develop and check a disaster recovery plan so in case of data loss or corruption you can recover quickly.

6. Purpose of Monitoring and Logging

The purpose of monitoring and logging is to use continuous monitoring to discover and fix security incidents as soon as possible.

• Enable CloudTrail and CloudWatch: AWS CloudTrail for logging API calls and AWS CloudWatch monitoring and alerting on suspicious behavior; guards the perimeter as well as detects change
• GuardDuty set up: Put AWS GuardDuty into operation continuously to monitor anti-hacking through unlawful activity.
• Log Retention Policies: Define log retention policies so logs are available when they're needed for forensic analysis.

7. Security Purpose of Network Security

Protect data in transit and make it rather difficult for anyone to access a small database.

• VPC endpoints use: Securely connect your VPC to AWS services without exposing data on the internet.
• Network Access Control Lists (NACLs): Use NACLs to control in and out traffic in your subnet.
• Security groups: Configure security groups so that only necessary traffic goes to and from your data lake resources.

Conclusion

How to establish a secure data lake is an essential job for financial institutions such as Starlight Financial. By using AWS services and adhering to best practices, your data lake can be made secure and scalable. Such exacting work pays off, though: practical advice is provided which lays the groundwork for consistent data security measures, freeing up time that you might spend on insightful and useful data development. Split up into points: Keeping data secure will be a top priority now that the importance of data is growing.