How to Protect Data Security

It is nothing new for enterprises to go to the cloud, and with the increase of business demand, more and more enterprises choose to deploy their business on multiple cloud platforms. According to the "Flexera 2020 State of the Cloud Report", multi-cloud environments are becoming the standard for enterprises, and 93% of enterprises are using this approach. Public cloud services used in multi-cloud strategies are becoming more and more popular, and Gartner predicts that revenue in 2020 will exceed $266 billion.



Sid Nag, vice president of research at Gartner, said in an official statement last year: "The next-generation solutions adopted are almost all cloud-enhanced solutions, which means that they are based on the advantages of cloud platforms to provide digital business functions."

Every next-generation solution brings next-generation security challenges. However, everyone's adoption of the cloud is not always security-centric. A multi-cloud environment requires multiple public cloud services, so the need for security is even more necessary.

80% of companies use public clouds to store sensitive data, but 52% of these companies have experienced data breaches. The multi-cloud approach does have many advantages, such as efficiency and cost savings, but security challenges still exist. Therefore, users need to understand the risks in order to get the most benefit from the multi-cloud strategy.

Next, I will introduce you to the 6 major security challenges that users may face in a multi-cloud environment, and related techniques to improve security best practices.

1. Rely on vendors to handle security

Cloud vendors do have relevant security measures to protect the security of the infrastructure. Many organizations generally believe that the security provided by vendors will cover user data and applications. Security is the shared responsibility of the supplier and the client, and the client of PaaS or IaaS bears greater responsibility. Users should understand exactly what the supplier’s security has protected, and cooperate with them to find the right security tools to protect data and applications.

2. Compliance with regulations

Most companies need to comply with data-related compliance requirements, industry standards, etc. As long as sensitive data is stored in the public cloud, compliance requirements may not be fulfilled. Users can place sensitive data on the server closest to internal control to meet regulatory compliance. In a multi-cloud environment, compliance efforts should be consistent.

3. Access Control

Too many employees can access cloud data and applications that are not related to their work. This provides convenient conditions for cloud abuse and cyber threats. Information technology (IT) teams should implement stricter controls and use identity and access management (IAM) tools to monitor permissions.

4. Visibility

Cloud services have almost unlimited scalability, and a multi-cloud environment can include dozens of platforms. But, can you see the entire environment? If your network surveillance program does not have a high level of visualization, it is equivalent to opening the door for those threats. Users should consider deploying tools such as security orchestration, automation, and response (SOAR) to improve incident response or security information and event management (SIEM). This will help collect real-time information throughout the environment, including log management and security event notifications.

5. Vulnerability Management

There are vulnerabilities in applications and software, and frequent testing is required to find these vulnerabilities. Through threat intelligence software, regular penetration testing and software scanning can be performed, thereby improving vulnerability management. Users should think of vulnerability management as locking the portal to prevent bad actors from easily accessing your environment.

6. Historical data protection

At present, many cloud security tools focus on the use of real-time data, and do not include historical data deeply stored in archives. Historical data may not comply with the new compliance rules or incorrectly labeled, making it more vulnerable to attacks. Best security practices for historical data include improved data classification to detect different levels of sensitivity, and the creation of data loss prevention (DLP) strategies to develop action plans in the event of a data breach. Make sure that the DLP tool is customizable, as standard templates may not suit your needs.

The multi-cloud environment presents unique challenges for security decision makers. Therefore, users must use excellent security measures to protect data from cybercriminals!