To prevent data breaches and cyber attacks, companies need to prioritize the security of sensitive data. One method of increasing the security of sensitive data is data masking.
Data masking is the process of changing sensitive data so that unauthorized people cannot access it. There are several data masking techniques, including randomization, substitution, shuffling, encryption, hashing, tokenization, and nulling. It is essential to identify why organizations should implement sensitive data masking.
Improved Data Security
Data masking will improve the organization’s data security framework. Applying techniques like substitution and encryption will reduce the risk of data breaches. Even if a cyber attack occurs, only masked data will be available in the system.
Furthermore, by implementing data masking, organizations can avoid insider threats. Employees, contractors, and third-party vendors often require access to data for testing, development, or support purposes. Giving access to data will introduce new risks to the organization. Data masking allows organizations to provide necessary data for these purposes without exposing actual sensitive information. This minimizes the likelihood of insider threats.
Compliance with Regulations
It is essential to adhere to data protection regulations if the organization is handling sensitive information. There are several data protection regulations.
- General Data Protection Regulation (GDPR)
- Health Insurance Portability and Accountability Act (HIPAA)
- Payment Card Industry Data Security Standard (PCI-DSS)
These regulations have strict requirements on how organizations manage and protect data. Non-compliant organizations can result in severe penalties, legal repercussions, and reputational damage.
Data masking will help organizations adhere to these regulations. For example, GDPR will force pseudonymization of personal data to enhance security. Furthermore, HIPAA requires healthcare organizations to de-identify patient information to prevent unauthorized access. Data masking can be used to comply with these regulations.
Maintaining Customer Trust
Especially in an organization where sensitive customer data is being used, it is critical to secure those sensitive data. A single data breach will prevent many new customers from joining a specific organization. For example, in the banking domain, if there is a customer breach in a specific bank, existing customers will try to remove their accounts from the bank. Also, potential customers will not join the bank. A single data breach can ruin an organization’s reputation.
When customers know their sensitive data is masked and secure, they are more likely to engage with an organization’s services and share their information. This trust is invaluable, as it fosters long-term relationships and will help build the image of that organization in the industry. On the other hand, organizations that fail to protect sensitive data risk losing customers to competitors who prioritize data security.
Reducing Costs
Data breaches can result in huge financial losses, including legal fees, fines, and remediation costs. For example, if a major retailer faced a data breach that exposed millions of customer records, it would result in huge legal fees, regulatory fines, and a decline in stock value.
Implementing data masking can help prevent these costly incidents by enhancing data security. Furthermore, managing real sensitive data often requires complex security measures and controls. Cyber insurance premiums can be high, especially for organizations handling large volumes of sensitive data. Data masking will help data management by reducing the need for complicated security protocols, making it more cost-effective.
Safe Data Sharing
In an organization, data sharing between multiple departments is very common. However, sharing sensitive data across departments, with partners, or in cloud environments can expose organizations to significant risks. Data masking allows safe data sharing by providing masked data.
Furthermore, testing with real data can lead to unintended exposure. By masking data, organizations can conduct testing without compromising sensitive information. Similarly, when collaborating with other stakeholders, masked data will ensure that privacy is maintained.
Wrapping Up
In conclusion, data masking is a critical tool for organizations aiming to protect sensitive information. By enhancing data security, ensuring regulatory compliance, maintaining customer trust, facilitating safe data sharing, and reducing costs, data masking provides so many benefits to the organization. As cyber attacks are increasing these days, it is essential to mask data to increase the security of sensitive data.