Today’s organizations have large amounts of data that they are gathering and accumulating. Although the data is essential for business activities, the volume and variety of the data lead to a critical problem of data privacy and security. Personal information, identity information (PII), and /or financial information getting into the wrong hands can have devastating effects. This not only affects consumer confidence but results in organizations incurring steep penalties, and, in other instances, suffering damage to their image.
This is where data masking tools come into play. The tools obscure sensitive data elements by creating a replica data set to minimize exposure risks. This article will explore the importance of data privacy and security, the functions of data masking tools, and how they can be used to set a robust data security system for an organization.
The Urgency of Data Privacy and Security
Data breaches are on the rise, there’s no doubt about it. According to sources, a whopping 6.41 million data records were leaked in the first quarter of 2023 alone worldwide. These breaches not only impact businesses but also cause significant distress to individuals whose data is compromised.
Additionally, stringent data privacy regulations, such as the General Data Protection Regulation, have placed organizations under increasing pressure to protect personal information of the people. These regulatory requirements require organizations to take strong data security measures and empower individuals to control their data. If these regulations are not followed, it can result in enormous penalties, the company’s reputation may suffer irreversibly, and this may even lead to a legal battle. Consequently, the issue of data security should not be regarded as an exclusive obligatory requirement of the legal sphere alone but also as a tool in establishing consumer confidence in the enterprise. Organizations are also adopting advanced solutions like unidirectional data transfer equipment, which ensures that sensitive information can only move in one direction, further reducing the risk of data leaks or cyber intrusions.
Unveiling the Power of Data Masking Tools
Data masking tools employ several techniques to convert sensitive data into disguised information, which preserves the data structure and the main statistical features but changes all of the values to fictitious ones. For instance, in Tokenization, sensitive data is replaced with a random, meaningless set of characters or codes, also known as tokens. In Shuffling, there is reordering of the characters within a data item but not in the format of that item.
There are various benefits of data masking tools. Among these is reduced risk of unauthorized access to sensitive data and identity theft. With data masking, even with a potential data breach, the masked data remains irrelevant to the intruders, who, therefore, are incapable of accessing personal information.
Data masking tools can also help organizations embrace the principle of data minimization found in privacy regulations. This means that adequate precautions are taken to keep only necessary data, which ultimately eases compliance. Implementing an ISO 27001 internal audit ensures that these practices are properly documented, assessed, and aligned with international information security standards.
With masking, organizations can share data with third-party vendors or with other departments in the same organization for the sake of analysis, testing, and training without risking the data's original information to get exposed.
Data masking can mitigate the risk of insider threats by limiting exposure to sensitive data, including phone numbers through phone number masking, with its original holder only. Authorized users can still work with the masked data for legitimate purposes.
Advanced Data Masking Capabilities
Modern data masking tools offer a range of advanced features that can meet various security needs. Some of these are listed below:
- Data Discovery and Classification- The tools can perform an automated discovery of databases, identify the types of sensitive data, and classify the data further based on the data privacy policies. These data discovery tools are essential for identifying where sensitive information resides within your systems, which is crucial for ensuring comprehensive data masking.
- Dynamic Data Masking- This technique masks data in real-time when the data is being accessed, ensuring that only the minimum necessary level of detail is revealed.
- Data Masking Policies- Granular data masking policies define which data is subject to masking rules and who has access to specific data based on user or role-based specifications.
- Auditing and Reporting- The data masking tools can audit the activities related to masking and even generate reports, which are helpful for compliance.
Though there are many tools suited for effective data masking in the market, you need to make different considerations when choosing the right one. For instance, cloud-based, on-premise, or hybrid deployment options can cater to different infrastructure needs. You need to check that the tool you’re thinking of using supports the specific data types that your organization collects and stores and is able to scale with growing data volumes for efficiency. You also need to look at the types of masking techniques used and ensure they meet your security requirements.
A Future with Improved Data Privacy
Data masking tools are essential for organizations navigating the ever-evolving data privacy landscape. Here's how data masking can help ensure a safer future-
- Masked data is suitable for conducting thoughtful analysis without exposing personal privacy. This aids the organizations in extracting valuable insights from data for dynamic and strategic business decisions, while maintaining the privacy of sensitive information.
- The use of data masking tools with data subject access request (DSAR) automation can help in assisting people in understanding their rights and how to gain access to their data as required by laws like General Data Protection Regulation.
- As cloud adoption gets more prevalent, so does the importance of data masking in securing sensitive data stored in the cloud. Tools can be integrated with cloud platforms for comprehensive data security.
- Data masking promotes secure collaboration between various organizations. As joint projects often require the exchange of datasets, data masking permits the organizations to mask these datasets such that their collaborative project does not expose sensitive information.
Data masking is not an absolute solution, but it can be contributed to the list of tools that will help in minimizing data breach. To do that, one has to proactively mask all the important data that cannot be revealed to an unauthorized person to reduce the threat of data breaches by many folds, and to gain trust from other parties, and to effectively meet data privacy regulation standards. Since there are expectations of enhancements in the data privacy regulations as well as the emergence of stronger data security threats in the future, data masking tools must closely determine a future where data will be used and secured rightly.
