Securing sensitive data in today’s digital world has become increasingly complex and challenging, especially if parties practice poor data management, network security, encryption methods, or endpoint protection. As cyber attacks continue to grow, it’s absolutely necessary to maintain stronger cybersecurity practices.
Whether on an individual or organizational level, it’s important to learn the primary methods for protecting sensitive or confidential data to avoid potential data breaches or data loss. Losing important data can be especially devastating, usually resulting in identity theft, loss of business, or exposure of classified information. This article discusses the best methods for protecting your most sensitive information.
What is Sensitive Data?
Sensitive data is important, confidential information that requires a higher level of data security to prevent unauthorized access from hackers or malware. Data deemed sensitive is typically protected from outside parties and should be inaccessible unless granted permission. Today, large corporations are subject to cybersecurity and data protection standards set by regulatory bodies like the USA’s Federal Trade Commission (FTC), the European Union’s General Data Protection Regulation (GDPR), or Australia’s Australian Cyber Security Centre (ACSC) to strengthen information security.
Examples of sensitive data include:
- Personally identifiable information (PII)
- Financial, banking, or credit card information
- Legal information
- Medical or protected health information (PHI)
- Biometric data
- Customer and employee data
- Internet browsing history
- Proprietary information or trade secrets
- Business operations data
- Classified government information
7 Best Methods for Protecting Sensitive Data
Here are the 7 best methods for securing and protecting your data:
1. Organize & Classify Data
Data classification is the process of organizing data into multiple categories within a system to make it easier to access and secure, rank by sensitivity, and reduce storage and backup costs. Organizing the data by risk level (low, medium, high) allows organizations to implement different security measures for each sensitivity level, as well as determine which information is public versus private.
Having a data classification policy in place can greatly reduce inefficiencies and create better safeguards for personal or company data. It helps an organization better assess how sensitive data is used and creates better data privacy and security for third and fourth parties.
2. Enable Data Encryption
Any organization operating with highly sensitive data should consider encryption to prevent unauthorized parties from accessing the data. Cryptographers code the data using complex algorithms and ciphers that protect data from being stolen or exposed. Even if the data were somehow intercepted or stolen, it would be near impossible to decode without a decryption key. Data encryption ensures that the message stays confidential during transmission and allows for authentication processes.
Government and military bodies have long used data encryption to transmit and receive classified communications. Anytime sensitive data is transmitted online, such as payment information or social security numbers (SSN), encryption helps secure that data. However, it’s important to note that encryption has limitations due to evolving technology like cryptographic attacks or the use of cloud storage. Although important, encryption should not be the only data protection tool used.
3. Perform Data Protection Impact Assessments (DPIA)
Any time data storage or data processing is involved, it’s important to assess and identify each and every potential risk before they occur. Data Protection Impact Assessments (DPIA) are live tools designed to help organizations secure their data if they involve significant risk to exposure of personal information. As of 2018, the GDPR has mandated DPIAs for any company that processes personal data as part of their compliance regulations.
As part of a DPIA, organizations must:
- Identify the nature, scope, context, and purpose of the data processing
- Assess what risks are involved for each individual or party
- Determine the necessity and proportionality measures for security risks
- Ensure security processes are compliant with regulations
A DPIA isn’t just a tool for assessing risk during data processing — companies can also use it to define data processing roles within the company, data flow between systems and individuals, and the security policy in the event of a cyber attack.
4. Use Data Masking / Data Obfuscation
Data masking is similar to data encryption, but the main difference is that it replaces the original data with fictional data to protect its security. While encrypted data will always have an encryption key to view the original data set, the original data is completely removed with masked data.
Organizations will typically use data masking processes for internal use to prevent developers, testers, or researchers from accessing sensitive data. They can also use data masking to test various security protocols, patch systems, and build new features without using real user data. Data masking provides an extra layer of security to protect against third parties or insiders.
5. Set Up Multi-Factor Authentication
One of the easiest types of data security practices to implement is password protection and authentication. Many large corporations suffer major data breaches that leak the login credentials of their customers, which can be easily found on the dark web. However, users can secure sensitive data by implementing 2FA (two-factor authentication) or MFA (multi-factor authentication).
The additional factors required for authentication enhance protection and limit data access for threat actors. In fact, a Microsoft report revealed that 99.9% of compromised accounts did not use MFA, and only 11% of enterprise accounts had MFA.
Many hackers use a brute-force cracking method to guess common usernames and passwords to gain access to accounts. On top of that, many users reuse the same usernames and passwords across multiple accounts, increasing their security risk. Users can quickly and easily protect themselves against most hacking attempts by using authentication protocols.
6. Create Data Backups
Data management and backup are the foundation of all security solutions. If a hard drive becomes infected with malware or a network becomes a victim of ransomware, users or companies can quickly restore a backup to minimize the damage. Ideally, data should be backed up at least once a week, if not daily, to protect against malicious hacking attempts.
A good backup strategy is the 3-2-1 rule: keep 3 different copies of your most important data on 2 different storage media (physical and cloud storage) and 1 copy offline or offsite for emergencies or disaster recovery.
7. Implement Stronger Network Security
Network security is a broad term describing using many different security solutions to better protect your sensitive data from being stolen or accessed. It helps create a secure IT (information technology) environment for users by preventing unauthorized access. Here are some of the tools you can use for better data security:
- Antivirus & anti-malware software
- Data loss prevention (DLP)
- Intrusion detection systems (IDS) & intrusion prevention systems (IPS)
- Virtual private networks (VPN)
- Endpoint response and detection (EDR)
- Network segmentation
- Secure data removal tools