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Data Masking vs Data Encryption: Differences and Use Cases

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Data masking and data encryption are two popular methods used to protect sensitive data in different scenarios. Although both techniques are designed to provide data security, they have distinct differences and use cases. In this article, we will discuss the differences between data masking and data encryption, as well as their respective use cases.

Data Masking

Data masking is a method of modifying data to make it unidentifiable while still retaining its functionality. This performance is used to protect delicate information by hiding it from unauthorised users while allowing approved users to access the data they need to perform their work.

In situations where delicate data needs to be shared for testing or research, data masking is usually used to protect that data. For example, in the healthcare industry, patient data is often shared with the seeker for analysis.

Still, patient privacy must be retained, and data masking can be used to replace sensitive content like patient names or social security numbers with fictitious beliefs while keeping the knowledge and format of the data intact.

Data masking is an expensive tool for safeguarding private information, and it has become increasingly critical in industries where data privacy regulations are strict. By masking sensitive data, companies can guarantee that their data is secure, decrease the risk of data breaches, and maintain the trust of their customers.

Data masking companies provide essential services to organisations seeking to protect their confidential information from potential data breaches and unauthorised access. By offering specialised data masking solutions.

These companies can help businesses hide or alter sensitive data to make it unintelligible and unusable to anyone who does not have the proper authorisation. Through their expertise in developing and implementing data masking techniques.

These companies can assist organisations in safeguarding their sensitive data while ensuring that it remains accessible and functional for authorised users.

Data masking companies use a variety of techniques to mask data, including:

  • Substitution: replacing sensitive data with fake data that looks and feels real but does not reveal any sensitive information.
  • Shuffling: rearranging the order of sensitive data so it becomes difficult to decipher.
  • Redaction: blacking out or removing sensitive information from documents or databases.
  • Tokenisation: replacing sensitive data with a token that is meaningless to anyone outside the authorised system.

Data Encryption

Data encryption relates to transforming plaintext into ciphertext such that it cannot be decrypted without the right decryption key. Protecting the privacy and integrity of data during sending or storage is the main goal of data encryption. Data tampering and alteration are both prevented via encryption, which also prevents unwanted access to the data.

In circumstances where sensitive data is sent across open networks, like the Internet, data encryption is frequently utilised. For instance, to prevent it from being intercepted and accessed by unauthorised parties, your credit card information is encrypted during transmission when you enter it on a shopping website.

Data encryption is a crucial aspect of recent data security, and several techniques are employed to encrypt data efficiently.

Here are some of the most common encryption techniques:

  • Symmetric Key Encryption: Also noted as secret-key encryption, it uses a single key to encrypt and decrypt data. Important information is shared between the transmitter and recipient of the data, ensuring that only authorised parties can access the data.
  • Asymmetric Key Encryption: Uses two opposite keys for encryption and decryption. The public key is used for encryption, while the private key is used for decryption. Asymmetric key encryption is widely used in secure communication rules like SSL/TLS.
  • Hashing: Hashing is a method used to generate an unusual code, or hash value, for a piece of data. The hash value is used to confirm the unity of the data and guarantee that it has not been altered or stepped on. Hashing is normally used in password storage systems, digital fashion, and message certification codes.
  • Advanced Encryption Standard: This is a widely used encryption formula that uses a block cipher to encrypt and decrypt data. AES is a symmetric key encryption algorithm that is used to secure data at rest, such as stored files and databases.
  • Transport Layer Security: This is a rule used to secure data sent over the internet, such as web traffic and email. TLS uses an increase in symmetric and asymmetric key encryption to guarantee data confidentiality, integrity, and authenticity.

Data encryption techniques play a vital role in protecting sensitive information from unauthorised access or use. Organisations can employ one or more of these techniques to encrypt data based on their specific security requirements.

Differences and Use Cases:

Data encryption and data masking are mostly employed for different purposes, which is the main distinction between them. By obscuring sensitive data, data masking primarily serves to conserve data privacy while still sanctioning authorised users to access and apply the data for legal purposes. On the other hand, data encryption is mostly used to safeguard the privacy and accuracy of data while it is being sent or stored, as well as to stop criminal access to it.

When it is necessary to share or use data for testing while protecting privacy, data masking is frequently used. Data encryption, on the other hand, is rarely used to protect data when it is stored in places where it may be defenceless to unauthorised access or when it is being transmitted over public networks.

Final Comment

Data encryption and data masking are both essential methods for safeguarding sensitive data. Data encryption converts plain, readable data into an unreadable format, whereas data masking alters data to make it untraceable while maintaining functionality.

Data masking is frequently used to protect data privacy while sharing or testing, whereas data encryption is frequently used to protect data confidentiality and integrity during transmission or storage.

Each technique has its own set of use cases. Organisations looking to safeguard their sensitive information from data breaches and illegal access can turn to data masking firms for specialist services.

They conceal sensitive data while still guaranteeing that it is accessible and usable for authorised users by using a variety of techniques like substitution, shuffle, redaction, and tokenisation.

7 Ways to Manage Fraud Within Your Financial Organisation

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Fraud is a serious problem for financial organisations of all sizes. According to the Association of Certified Fraud Examiners, the typical organisation loses 5% of its annual revenue to fraud. But you can take steps to protect your organisation and reduce your fraud risk.

Here are seven ways to do just that:

SAP Fraud Management

Why not partner with the world’s leading provider of enterprise application software? SAP offers a comprehensive suite of solutions to help organisations quickly detect and efficiently resolve fraud cases. And because SAP integrates seamlessly with popular accounting and ERP systems, you can be up and running quickly and with minimal disruption to your business operations.

SAP fraud management is a critical solution for organisations looking to protect themselves from the costly effects of fraud. With its comprehensive suite of tools, SAP can help you detect and prevent fraud before it happens.

To learn more about SAP fraud management, visit the Pathlock website, the only solution endorsed by SAP.

Implement Internal Controls

One of the best ways to combat fraud is to put internal controls in place. Internal controls are procedures or policies designed to prevent or detect errors or irregularities. They can be as simple as requiring two people to sign off on all disbursements over $500 or regularly reviewing expense reports for unusual activity.

The key is having appropriate organisational controls which will deter or detect fraud. You also must ensure your employees know the controls and how to comply with them.

Conduct Background Checks

Another way to reduce fraud risk is to conduct background checks on all employees, contractors, and vendors. These checks can help weed out individuals with a history of fraud or financial crimes.

You should also have a policy for what to do if an employee is convicted of a crime. For example, you may require the employee to repay stolen funds and terminate employment.

Educate Your Employees

Educating your employees about fraud and how to spot it can go a long way in preventing it from happening in your organisation. Ensure your employees know what types of fraudulent activity to look for and who they should report it to if they see something suspicious. You might also consider implementing an anonymous tip line where employees can report suspected fraud without fear of retaliation.

You can also provide employees with training on specific fraud risks, such as phishing scams or identity theft. This will help them be more vigilant in spotting these scams and protect your organisation from becoming a victim.

Use Technology

Technology can be a powerful tool in the fight against fraud. Consider investing in accounting software that includes built-in controls and safeguards or implementing spend management tools that provide real-time visibility into how money is being spent within your organisation. SAP fraud management is also a worthy investment.

You can also use data analytics to detect fraud. For example, you might flag any vendor payments significantly higher or lower than the average payment amount or any employee expense reports with unusually high amounts for meals or travel.

Technology can make it easy to monitor financial activity closely. This can be done through regular reviews of financial statements, expense reports, and other financial documents.

Look for red flags like unusual patterns of activity, significant or unexplained discrepancies, or transactions that don’t make sense. If you see something suspicious, don’t hesitate to investigate further.

Review Your Insurance Coverage

Be sure your organisation has adequate insurance coverage in place in case of fraud or theft. Many insurance policies will cover some or all losses incurred due to fraudulent activity. Review your policy regularly to ensure you have the coverage you need and that it is up to date.

You should also have a plan for what to do if fraud occurs. This should include who to contact, how to report the scam, and what steps need to be taken to mitigate the damage.

Use Data Encryption

Another way to reduce fraud risk is to use data encryption. This can help protect your organisation from data breaches that could lead to fraud. Data encryption scrambles data so it can’t be read without the proper authorisation and password. This makes it difficult for hackers to steal and use your data for fraudulent purposes.

Ensure all sensitive data, such as credit card and Social Security numbers, are encrypted. You should also encrypt electronic data via email or instant message.

Take Away

Fraud is a serious problem that can have a devastating effect on your bottom line—but there are steps you can take to protect your organisation from becoming a victim. By implementing internal controls, conducting background checks, educating employees, leveraging technology, reviewing your insurance coverage, and partnering with SAP, you can help reduce the risk of fraud and keep your business safe.