12 Tips to Protect Company's Data

According to Statista, 353 million people in the US from 2005 to 2023 became victims of data leaks, breaches, or exposure. There’s a big chance that many won’t ever return to the company that leaked their data, and why would they? In the digital era, data privacy is everything, and companies need to implement the best practices possible to protect it. The increase in the number of breaches from 2022 to 2023 was more than 43%, making it a record year for data compromises, particularly driven by the rise in sophisticated cyberattacks and the persistence of human and system errors.

Data leaks and breaches can happen to any company, and it doesn’t matter whether you're a small SaaS startup, medium company or a unicorn. It is estimated, medium-sized businesses are heavily attacked, particularly through supply chain breaches, which surged by over 2,600% since 2018. These companies often serve as intermediaries in larger networks, making them appealing targets for attackers who seek to exploit broader vulnerabilities.

However, there are universal data security practices that will help to protect your users’ personal information regardless of your size, amount of resources, or the type of your services. We created a list of 12 tips and market practices to ensure that the data of your customer is as safe as possible. Dive in!

1. Data Encryption All sensitive data should be encrypted using robust encryption standards such as AES-256 for data at rest and TLS 1.2 or higher for data in transit. Use a secure and compliant key management system (KMS) for handling encryption keys. Use services which provide reliable solutions that ensure keys are stored and managed securely, with automated key rotation and auditing capabilities.

   
   

2. Working Environment Any company should educate all team members about the basic rules of digital hygiene: don’t connect to public WiFis, don’t insert suspicious flash drivers, and don’t leave your laptop unattended.

   
   

3. Following the Set Internal Processes Companies should always monitor whether the data protection rules are actually being followed. If not, they will get scattered processes and no improvements even when a new system is introduced. Management must clearly state to all team members that new processes must be followed and show that they will be beneficial to all parties within the company.

   
   

4. Cloud Storage Solutions Use cloud services for their security features, scalability, and compliance certifications, and take advantage of the built-in encryption, access control, and compliance with regulations like PCI-DSS and GDPR (universal data protection standards). Choose data storage regions that comply with local data residency laws, ensuring that data is stored within the appropriate geographic boundaries to meet regulatory requirements.

   
   

5. Financial Regulations Compliance Ensure that your data storage solutions comply with PCI-DSS standards. This includes using strong encryption, maintaining secure access controls, and regularly auditing your security practices. If your region is covered by GDPR or CCPA, ensure that data storage practices include user consent management, the right to be forgotten, and stringent data protection measures. A very important topic on the regulatory side of data storage is the Service Organization Control 2 (SOC 2). This is a framework established by the American Institute of Certified Public Accountants (AICPA), and it’s designed to ensure that service providers securely manage data to protect the privacy and interests of their clients. SOC 2 is particularly relevant for SaaS companies, cloud service providers, and any organizations that handle sensitive data on behalf of their clients. The main purpose of SOC 2 is to provide assurance to clients and stakeholders that a service organization has the appropriate controls in place to protect their data. It’s often used as a standard for data security and compliance, particularly in industries like technology, healthcare, and finance.

   
   

6. Access Control and Identity Management Implement Role-Based Access Control (RBAC) to ensure that only authorized personnel have access to sensitive data, and minimize the risk of data breaches by limiting access based on roles and responsibilities. Require Multi-Factor Authentication (MFA) for accessing data storage systems to add an extra layer of security.

   
   

7. Data Backup and Disaster Recovery Implement regular, automated backups of all critical data. Use geographically redundant storage to ensure that data can be recovered in the event of a disaster. Develop and regularly test a disaster recovery plan to ensure that you can quickly restore operations in the event of data loss or a security incident.

   
   

8. Database Security First of all, you need to pick the right database. Ensure that database instances are secured with firewalls, access control lists, and encryption. For highly sensitive data, consider using data masking or tokenization. This helps protect data by replacing sensitive information with anonymized values or tokens. In the input phase, when you upload the data to the database, make sure that the connection is secure, ideally, it should be a local network connection. In the storage phase, use strong encryption algorithms (like AES-256), and monitor database activity like accesses and changes, alerting administrators to unusual activities like unauthorized access attempts. Lastly, in the access phase, use TLS/SSL encryption for all connections between the database and clients to protect data while it’s being transmitted.

   
   

9. Audit Logging and Monitoring Implement audit logging to track access and modifications to data. Logs should be stored securely and reviewed regularly to detect and respond to any suspicious activity. Use real-time monitoring tools to detect unusual patterns or potential security breaches. This enables quick responses to potential threats and helps maintain the integrity of your data storage systems.

   
   

10. Zero Trust Architecture Implement a zero-trust security model where no user or system is trusted by default. This approach requires strict verification of all users, devices, and connections before granting access to data, ensuring that even internal threats are mitigated.

    
    

11. Software and Libraries Management Quite often we see that software and 3rd party libraries the companies use for development purposes can be vulnerable to cyber-attacks and have backdoors in them. So updating and making scans for software/libraries is a must to keep the development infrastructure secured.

    
    

12. Use Technologies High-quality data security will take a lot of financial, human, and time outlay. As a rule, big companies dedicate multiple teams of developers to manage data security, while small startups and even medium-sized companies aren’t able to dedicate that many resources to data protection, minimizing the costs and maximizing the reliability. To ensure that the data is stored safely, many companies resort to the innovations in the data protection sphere, in particular preferring to trust Data Security to AI technologies. What prevails here is the speed of information processing, the ability to process complex data sets, identify patterns and generate insights that might take human analysts weeks or even months to discover. AI can significantly reduce human errors, especially in repetitive and complex tasks like finance, and manufacturing, and automate business processes. As having a data-engineering team can be very expensive, AI can consider the reduced cost of managing it.

In the modern world, protecting your data is essential for any company, and is directly connected to its success and reputation. Following the best market practices and “digital hygiene” is something your company must have and convey that message to all team members. Companies that also adopt new technologies in the data protection sphere can gain a significant competitive advantage by being able to innovate faster and operate more efficiently, spending less operational resources on data protection, and getting higher-quality results.