The digital world is full of opportunities provided by the Internet, as well as cloud servers, when it comes to hosting, sharing and using the profusion of data that is becoming increasingly abundant and valuable to users and businesses around the world.
What is data masking and why is it so important?
Data masking creates a realistic replica of an organization's data, so that this new version cannot be decrypted or reverse-engineered in an attempt to steal any confidential information.
This process, at the heart of any digital security strategy, protects sensitive or private data while offering a functional alternative in cases where it is not necessary or relevant, such as in software development and testing.
The main advantages of data masking
Data masking carries out an anonymization process designed to mitigate the ability to trace data or electronic tracks that would lead to the misuse of data or the disclosure of personal details. It therefore offers the following benefits for businesses:
- Prevents data from circulating openly in non-productive environments and, as so often happens, ending up succumbing to critical internal or external threats, such as leakage, misuse, or theft.
- Allows data sharing with authorized users in a secure manner, ensuring that production data is rendered unusable to any attacker seeking to exploit it.
- Reduces the risks associated with data hosting in the cloud or insecure interfaces with easily hacked third-party systems.
- Minimizes security costs: increases workflow efficiency in order to work in compliance with the GDPR and other data protection regulations, and strengthens the privacy protection of the entities and individuals involved to the maximum.
How does data masking work?
The data masking process alters the data values while respecting the same data format. The manner of altering the data will depend on the nature of the data, and may include, among other types of anonymization, a masked word identifier, word substitution, or data encryption using empty spaces or blocks to hide the words.
Regardless of the type and technique used, companies must start by identifying all confidential data to later use algorithms that mask these data and replace them with others that are structurally identical.
The main uses of data masking
A robust data masking solution will be aimed at protecting different kinds of data; from personal or protected health data, to payment and intellectual property information. The use of data masking systems provides many diverse applications in the business world.
Optimization of the anonymity system
In order to automate the identification and replacement of sensitive information in the workflow, anonymization tools such as the Pangeanic Masker can store, use, share and monetize data in a simple way by using configurable artificial intelligence and learning systems for anonymity.
This offers an effective way to optimize communication between organizations and protect the client's trust when it comes to sharing data, as well as saving time and money.
Compliance with privacy standards
To manage the risk of losing millions of dollars, reduce social liability and avoid the fines associated with a data breach, companies use data mining as a secure method of complying with privacy standards (such as CCPA / CPRA, HIPAA, GDPR or APP) by leveraging the anonymization solutions created for public administrations.
Use of different formats
Anonymization is available for numerous types of data sources, both structured and unstructured, including the following popular formats:
- Text files: word processing, PDFs, spreadsheets, presentations, emails, logs, etc.
- Social networks: data from Facebook, Twitter, LinkedIn, etc.
- Commercial applications: MS Office documents, productivity applications, etc.
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Practical data masking applications
To avoid being the subject of negative press, class-action lawsuits or cautionary tales, organizations around the world use different types and techniques of data masking to ensure data security.
The most common data masking techniques
- Identification labels replace data with a data tag.
- Substitution replaces data with a temporary and realistic identifier.
- Data blending exchanges values within the same dataset.
- Gaps replace data with blank spaces.
- Redaction replaces data with a solid black line.
- Encryption requires a unique key to unmask the data and is the most secure way to protect information.
Legislation to be taken into account
With the introduction of increasingly stringent international privacy standards, organizations have a greater responsibility to protect the personal data of subjects including customers, employees and prospects.
The European regulation relating to the protection of natural persons was put in place in 2018, with the aim of protecting natural persons with regard to the processing of their personal data and the free movement of such data. Fines for non-compliance with the GDPR can be up to 20 million euros.
In order to comply with this legislation, companies must obtain express and unequivocal consent for the use of the data, specify what data they are using, how they are processing it, for what purpose and who the person responsible for it is.
Legislation in the United States and Japan
Although the United States and Japan are many steps behind Europe in terms of data protection, the California Consumer Privacy Act (CCPA) came into force in the United States in 2020, and Japan's Personal Data Protection Act (PDPA) has already adopted a number of amendments that plan to come into force in 2022.
It is, therefore, essential to adhere to the current standards and, above all, never sidestep the obligations, for both ethical and legal reasons. Bad practices can jeopardize your business's reputation and lead to multimillion-dollar lawsuits that can put your company on the line.
Pangeanic, your strongest ally when it comes to data masking
It automatically identifies insider information and customizes functions specific to your business needs; adjusting the level of sensitivity and choosing unique tags to optimize the way the different types of anonymization are performed. What are you waiting for? Try it now or contact us to find out more.