When diving into proactive database security strategy, think over sensitive data masking features as a part of multi-level database protection.
This article will cover data masking as a proper solution to secure sensitive data kept in a company, data masking classification as well as introduction to data masking process. Though, before that let’s make it clear what sensitive data is.
The concept of data sensitivity is used to describe a measurement of data confidentiality requirement. Data is classified as per severity of damage that is caused by its unauthorized disclosure and level of recovery after data leak. Roughly speaking, data breach may lead to minor loss and require an administrative action to recover or result in a significant damage in money, property, law infringement and end up with a legal action.
Typical consequences of confidential data losses:
– Lawsuits. Sensitive data protection is demanded by governing standards. There are plenty of regulatory standards that provide data privacy and security provisions for safeguarding sensitive information. Let me clarify that this data may include, for example, information specific to person’s identity: address or phone number, credit card numbers, bank details, medical data, online identifiers and many more.
– Ransom. As an example, consider a ransomware that locks your data. The way to restore access to it is to pay huge amount of money to a hacker to settle this database attack. And even after that there still be the risk to be hacked again.
– Risk to your business. By this I mean data leak to competitors as well as spoiled company’s reputation.
The problem that an organization usually encounters is non-production environment security, i.e. when a database has to be shared with testers, developers, outsource companies, etc. The question is who has access to the database with sensitive data in it and who has not. To be more exact what to do if professional duties require having access to a functioning database but do not allow to actually see sensitive data. No one knows what vulnerability can be exploited. What does a hacker need? That’s right. To find a “loophole” in your database. Is everyone in a development or quality assurance team in your circle of trust? Doubt that.
The aim is to have a fully-functioning database for non-production purposes with no risk to disclose sensitive information and jeopardize company’s business. Here comes a good and effective solution – data masking. To clarify the data masking process, let’s consider a database security solution – DataSunrise Data and Database Security Suite with built-in Dynamic Data Masking and Static Data Masking instruments.
Data masking is obscuring sensitive information within your production database. DataSunrise Data Masking can be done either statically or dynamically. To perform static data masking, it is required to make a replica of a database identical to an original one except to fields that are to be masked or faked. The dummy database does not somehow influence its functionality and it is enough to simulate a database for testing or developing, etc. Notice though you will have to think about additional hardware resources to store this duplicated database and update it every now and then as per database alterations made in present. An advantage is obvious: no sensitive data leaves your database unconcealed.
DataSunrise Dynamic Data Masking conceals confidential data in real time. When a query is sent to a database, DataSunrise captures and modifies it on-the-fly according to masking policies and then redirects it to the database. Intact sensitive data is available only to authorized users, and non-privileged users see either fake or cloaked data instead of an original one.
DataSunrise Data and Database Security Suite can also function as a regulatory compliance instrument to obey such privacy standards as GDPR, HIPAA, ISO 27001, SOX and PCI DSS. First, sensitive data is found by an integrated Sensitive Data Discovery feature. As soon as it is located, the Regulatory Compliance Manager feature creates authorized and non-authorized roles for DB users that have and do not have access to sensitive data accordingly.
Now you know how to mask sensitive data in your database to ensure reliable database security strategy: just mobilize a security squad – dynamic or static data masking.