Data is distinctive and vital, unlike operating systems and applications that can be reinstalled. It holds significant importance on your computer or network.
According to IEEE Senior Member Kayne McGladrey, organizations need to maintain strong privacy measures, a clear privacy policy, opt-out processes, and compliance with consumer protection laws to reduce financial and reputational risks.
Below are 10 strategies you can employ to defend your data from unauthorized access and loss.
1. Safeguard everything with passwords
Using passwords to protect your data is the primary defense against unauthorized access. It also enhances the security of your systems by combining password protection with other security measures. Some businesses must implement password protection to comply with regulations such as the General Data Protection Regulation.
Implement a stringent password policy to secure your business data. Ensure employees create complex passwords and update them regularly.
2. Regularly back up data
Backing up data consistently and early is a crucial element of a data loss prevention strategy. Data loss can occur due to cyberattacks, natural disasters, human error, among other reasons. By backing up your data, you can recover it after a data loss event.
In addition to manual backups, consider utilizing data backup solutions that automate the process based on your configured schedule. Advanced backup solutions allow you to select the data for backup.
3. Maintain up-to-date business software
Keeping your business software current ensures it receives the latest security patches, bug fixes, and updates to combat new and existing cyber threats effectively. As most cyberattacks exploit newly discovered vulnerabilities, it is vital to regularly update your business software to the newest version.
SEE: Threat actors jailbreak generative AI to use it to craft phishing emails, ignoring safeguards.
4. Employ a VPN
Virtual private networks are excellent for securing business data. A VPN establishes an encrypted tunnel for your data, shielding it from hackers and other malicious entities while reducing your online footprint.
For employees connecting to business networks or accessing sensitive files remotely, a VPN is essential. While a free VPN service can be used, investing in a paid VPN subscription from a reputable provider is recommended. Paid VPN services offer more reliable connections, dedicated servers, and premium features.
5. Deploy antivirus software
Modern antivirus software aids in safeguarding data against ransomware, spyware, Trojan horses, browser hijackers, and other cyber threats. While there is a cost involved for a business antivirus software license, it is a worthy investment to keep your data secure.
Windows 10 or higher versions come with built-in antivirus software. Although Mac computers have a closed ecosystem and built-in malware protection, additional antivirus protections can be purchased separately.
Amid the age of generative AI, antivirus protection is even more critical. Threat actors may use AI models in attacks, and malicious data could contaminate the model if it is used for training.
According to Ravi Srinivasan, the CEO of data protection company Votiro, “Once it’s malicious content, the AI agent that you’re trying to train is going to learn using malicious content as well.”
6. Utilize multifactor authentication
To enhance data protection, employ multi-factor authentication on devices connected to the business network. MFA requires users to enter a password and a one-time passcode sent to another device to access the system. This ensures that users need at least two devices or “factors” for login.
MFA serves as an additional security layer for your data and is increasingly crucial in business cybersecurity protocols. Without MFA, your data is vulnerable to unauthorized access resulting from lost devices or stolen credentials.
Even if organizations adopt a passwordless approach, MFA remains essential for external users, third-party contractors, and service providers still utilizing passwords by default. Hence, MFA should be viewed as part of the access solution within tech organizations.
SEE: Here’s everything IT leaders need to know about multifactor authentication.
7. Implement a public key infrastructure
A public key infrastructure manages public/private key pairs and digital certificates. Given that keys and certificates are issued by a trusted third-party (certification authority), certificate-based security is robust.
You can safeguard shared data by encrypting it with the public key of the intended recipient, which is publicly available. Only the holder of the private key corresponding to that public key can decrypt it.
8. Conceal data using steganography
Steganography programs enable you to hide data within other data. For instance, you could embed a text message in a .JPG graphics file or an .MP3 music file or within another text file, though the latter is challenging since text files lack redundant data for hiding messages.
As steganography does not encrypt the message, it is often paired with encryption software. The data is first encrypted and then concealed within another file using steganography software.
Various steganographic methods necessitate a secret key exchange, while others utilize public and private key cryptography.
A well-known illustration of covert communication software is StegoMagic, a no-cost download that can cipher messages and conceal them within .TXT, .WAV, or .BMP files.
The concealment of information can be especially crucial if according to IEEE member Rebecca Herold, “The institution utilizes authentic personal information (from clients, patients, staff, and others) for testing and/or training AI tools.”.
9. Enhance your knowledge and that of your staff regarding cybersecurity
An essential measure in safeguarding your information is educating yourself and your personnel on cybersecurity. It is important to foster a cautious approach when engaging with unfamiliar websites, emails, or messages; this includes grasping the significance of adhering to the recommended methods for safeguarding data, such as refraining from opening emails from unfamiliar sources and avoiding clicking on suspicious attachments.
SEE: Take advantage of this cybersecurity training bundle from TechRepublic Academy.
10. Look for expert consultation
You could engage security advisory firms to evaluate the security weaknesses in your system and provide solutions for addressing them.
If you require more comprehensive safeguards for your data, contemplate enlisting the services of a managed security solutions provider; they offer an array of security services, including around-the-clock security monitoring and incident management. Moreover, if you wish to insure your digital assets, think about procuring a cybersecurity insurance policy.
Generative AI ushers in novel data confidentiality concerns
Despite the fact that generative AI must adhere to the same principles, this trendy new technology introduces fresh data privacy issues as well.
“Every business that incorporates AI confronts an unmatched privacy hurdle: essentially erecting a connection between the company’s proprietary data and public AI models,” said Oliver Friedrichs, CEO and co-founder of cybersecurity company Pangea, in an email to TechRepublic.
Authorization is crucial in the realm of AI.
“In 2025, a troubling trend emerges where exposure of sensitive information through AI is not predominantly attributable to sophisticated assaults – rather, it transpires due to fundamental oversights in permission and data access controls,” remarked Rob Truesdell, Chief Product Officer at Pangea, via email. “Organizations are realizing that their AI systems are unintentionally disseminating confidential information simply because they have not stipulated who should have access to what.”
Srinivasan emphasized that transitioning to AI mandates data privacy considerations beyond what organizations contemplated before 2022; specifically, organizations may utilize business information to train in-house models. Companies need to be conscious of data masking or anonymization to prevent sensitive data from surfacing in the model’s results.
Organizations should consider, “How can you protect privacy prior to training the model?” Srinivasan inquired.
McGladrey suggested that transparency regarding the capabilities and limitations of generative AI is pivotal, as is compliance with state and federal privacy directives.
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