Data anonymization, masking, and key salting

Data anonymization refers to the process of protecting private or sensitive information by deleting or encrypting personal identifiers from data records. The process enables organizations to use vast amounts of data while safeguarding users’ privacy.

In AWS, you can anonymize your data using services like AWS Macie. AWS Macie uses machine learning to automatically discover, classify, and protect sensitive data like Personally Identifiable Information (PII).

Data Masking

Data masking is the process of obfuscating specific data elements within data stores to ensure that sensitive data is replaced with realistic but not real or identifiable data, rendering the data meaningless to those who shouldn’t have access to it.

One typical example of data masking is in a testing environment where the development teams need to deal with certain realistic data without breaching any privacy policies. They prefer to use the data which is close to real production data, but they don’t want to compromise privacy.

AWS’s Redshift is a fully managed data warehousing service that you can use to mask your data. For instance, you can create a view in Amazon Redshift, which lets users see the data they need to see, but masks particular sensitive data.

Key Salting

Key salting refers to the addition of random data (“salt”) to a password before processing it and storing it in a database. Salting improves data security because it makes it difficult for an attacker to steal data using a “rainbow table” attack (an attack that uses a precomputed table for reversing hash functions).

For key salting, AWS offers services like AWS Key Management Service (KMS). AWS KMS allows you to create, control, and implement symmetric and asymmetric cryptographic keys for your AWS services that are secure and easy to use.

The following table summarizes these concepts and their usages:

In conclusion, understanding the concepts of data anonymization, data masking, and key salting is crucial for preparing for the AWS Certified Data Engineer Exam. Not only do these principles help ensure data privacy and protection, but they also provide multiple avenues for maintaining secure and efficient data operations in AWS.

Practice Test

True or False: The primary goal of data anonymization is to protect people’s privacy by making it impossible to tell who the data is about.

• Answer: True

Explanation: Data anonymization is a process that transforms or removes personally identifiable information from the data so that people whom the data describe remain anonymous.

What is the main benefit of data masking?

• Maintain data accuracy
• Protect sensitive data
• Enhance data quality
• Increase data volume
• Answer: Protect sensitive data

Explanation: Data masking is a technique to protect sensitive information by replacing it with fictitious yet realistic data. It is often used when data needs to be shared for testing or analysis but contains sensitive information.

Which of the following best describes key salting?

• A procedure to hide keys within the data
• A method of key protection using spurious data
• A process to enhance the security of cryptographic techniques
• A system to organize keys for easy access.
• Answer: A process to enhance the security of cryptographic techniques

Explanation: Key salting involves adding random data, also known as a salt, to the input of a hash function to increase the security of the resulting hash.

Which of the following is NOT a technique for data anonymization?

• Data Swapping
• Data Masking
• Key Salting
• Data Perturbation
• Answer: Key Salting

Explanation: Key Salting is a technique used to enhance the security of cryptographic techniques rather than a data anonymization method.

True or False: Using data masking, it is impossible to retrieve the original data.

• Answer: False

Explanation: Data masking allows you to retrieve the original data. The masked data can be reverted to the original data using the right masking and unmasking algorithm.

In AWS, which service can help you analyze data at scale without worrying about data privacy since it automatically anonymizes all datasets?

• Amazon Athena
• AWS Glue
• Amazon Personalize
• Amazon Macie
• Answer: Amazon Personalize

Explanation: Amazon Personalize is a machine learning service which anonymizes all datasets by default, allowing you to analyze end-user behavior without any privacy issues.

True or False: Unsalted keys are more secure than salted ones.

• Answer: False

Explanation: Salted keys are more secure because the added random data (salt) results in a unique hash, even if the original input (password) is the same. This makes it more difficult for attackers to guess the original input by brute-force techniques.

Data anonymization ensures data:

• Inequality
• Integrity
• Quality
• Privacy
• Answer: Privacy

Explanation: Data anonymization processes are designed to prevent the identification of individuals in an analyzed data set, thus ensuring privacy.

Key salting in AWS can be utilized in which of the following AWS services?

• S3
• KMS
• Redshift
• All of the above
• Answer: All of the above

Explanation: AWS KMS allows you to create and control the cryptographic keys used to encrypt your data. These keys can be configured to include a salt for additional security. In S3 and Redshift, data can be encrypted using salted keys.

True or False: Data Masking is an irreversible process.

• Answer: False

Explanation: Data Masking is not always irreversible. Some methods of data masking allow the original data to be retrieved or unmasked.

Which of the following can be used in AWS to detect and protect sensitive data?

• AWS WAF
• Amazon Macie
• Amazon Rekognition
• AWS CodeStar
• Answer: Amazon Macie

Explanation: Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS.

In AWS, which encryption method uses key rotation?

• AWS Key Management Service (KMS)
• AWS Identity and Access Management (IAM)
• AWS CloudTrail
• AWS Elastic Load Balancing (ELB)
• Answer: AWS Key Management Service (KMS)

Explanation: AWS Key Management Service (KMS) makes it easy for you to create and manage cryptographic keys and control their use across a wide range of AWS services. It uses key rotation for enhanced security.

True or False: Data anonymization functions by substituting all the private, personally identifiable information in a data set with other data.

• Answer: True

Explanation: Data anonymization is a type of information sanitization with the intent to protect privacy. The process converts clear text data into encoded data, with the purpose of protecting sensitive data while preserving the data’s usability.

Data anonymization, masking and key salting ensure _____.

• Data redundancy
• Data protection
• Data duplication
• Data weighting
• Answer: Data protection

Explanation: All these methods are used to protect sensitive data during analysis, transport, or storage.

True or False: Data anonymization and data masking are interchangeable.

• Answer: False

Explanation: Although they both aim to protect sensitive information, data anonymization ensures the data cannot be connected back to an individual while data masking replaces sensitive information with fictitious yet credible data, which can be reverted.

Interview Questions

What is data anonymization in AWS?

Data anonymization in AWS refers to the process that removes personally identifiable information from data sets to protect privacy. AWS provides services such as Macie that can identify and help anonymize sensitive data.

What is data masking in AWS?

Data masking is a technique of creating a structurally similar but inauthentic version of an organization’s data that can be used for software testing and user training. Redshift can be used in AWS to mask data.

What is key salting in AWS?

Key salting is a process of adding random data to the input of a hash function that is used in protecting password or encryption keys. AWS Key Management Service can be utilized to manage cryptographic keys including salted keys.

Which AWS service can help automate data discovery and data privacy tasks?

AWS Macie is a fully managed data privacy and security service that can help automate data discovery and data masking tasks.

In the context of AWS, how are database snapshots encrypted?

Database snapshots in AWS are encrypted using AWS Key Management Service (KMS). Both the original snapshot and any subsequent copies are encrypted using the same KMS key.

What is the relevance of AWS Glue in data anonymization?

AWS Glue is a fully managed ETL service that can be used in data anonymization to make the data ready for analytics by removing personally identifiable information or obfuscating it.

How can you ensure decryption control of AWS KMS encrypted data?

By using AWS KMS, you maintain full control over who can decrypt your data. The control is established through Key policies that specify who can manage and use your keys.

What is the function of AWS DMS in terms of data security?

AWS DMS (Database Migration Service) can help migrate databases to AWS securely. It can replicate your source database for minimal downtime during migration ensuring the secure transition.

What is the use of AWS Secrets Manager?

AWS Secrets Manager helps to protect access to your applications, services, and IT resources. It allows you to easily rotate, manage, and retrieve database credentials, API keys, and other secrets throughout their lifecycle.

What does the data loss prevention (DLP) solution in AWS do?

The data loss prevention (DLP) solution in AWS helps identify and protect sensitive data such as personal identifiable information (PII) stored in Amazon S3, ensuring such information is not leaked or used improperly.

What is the role of an AWS KMS customer master key (CMK) in data encryption?

AWS KMS customer master key (CMK) is a logical key that is used to control access to and encrypt data. Using AWS KMS, you can create, control, and manage CMKs.

What is the process of pseudonymization in AWS?

Pseudonymization in AWS is a process that replaces private identifiers with fictitious data or pseudonyms. It helps reduce the risk of data breaches by ensuring the individuals represented in the data cannot be identified without additional information.

Which AWS service can help with event-driven security automation?

AWS Security Hub can help with event-driven security automation. It provides you with a comprehensive view of your security state and helps you check your compliance with the security industry standards and best practices.

What is the purpose of AWS Shield in data security?

AWS Shield is a managed Distributed Denial of Service (DDoS) protection service that safeguards web applications running on AWS. AWS Shield provides seamless DDoS protection, which allows you to maintain application availability and meet data security standards.

How can AWS SageMaker assist with data privacy?

AWS SageMaker can assist with data privacy by allowing you to remove or obfuscate sensitive information before using the data for model training. Additionally, SageMaker offers built-in algorithms that are capable of preserving privacy when dealing with sensitive data.