Big Data Cloud Security Strategy 4 Tips

The combination of cloud computing and big data can be said to be a match made in heaven. Big data requires a flexible computing environment, which can be expanded quickly and automatically to support massive amounts of data. Infrastructure cloud can accurately provide these requirements. But whenever we discuss cloud computing, we cannot avoid the following questions:


What is the cloud security strategy for big data?

When referring to cloud security strategies in big data use cases, we hope that any security solution can provide the same flexibility as the cloud without affecting deployment security. When transferring big data to the cloud, the following four tips can allow users to enjoy the flexibility of cloud computing and obtain strict cloud security policies.

1. Encrypt sensitive data (strongly recommended)

Data encryption will create a "virtual wall" for your cloud infrastructure. Deploying cloud encryption measures is considered the first step, but they are not suitable for all solutions. Some encryption solutions require local gateway encryption, which does not work well in the cloud big data environment. There are also solutions (for example, data encryption by cloud service providers) that force end users to trust those who have the keys, and these inherently contain dangers and weaknesses.

Some recent encryption technologies, such as split-key encryption, are very suitable for cloud computing. Users can keep the key in their hands while enjoying the advantages provided by the infrastructure cloud solution, keeping the key in a safe state. In order to get the best encryption solution for your big data environment, it is recommended to use split key encryption.

2. Looking for cloud security solutions that can be structurally expanded

In big data, every component of the structure should be able to expand, and cloud security solutions are no exception. When choosing cloud security solutions, users need to ensure that they can play a role in all cross-regional cloud deployment points. In addition, they must be able to scale efficiently in the big data infrastructure. On the surface, this does not involve hardware issues. However, because hardware security modules (HSM) are not scalable and cannot adapt to the cloud model flexibly, they are not suitable for big data use cases.

In order to obtain the necessary scalability, it is recommended to use cloud security solutions designed specifically for cloud computing, their security can be equivalent (or even more than) hardware-based solutions.

3. Realize the greatest degree of automation

The inability of cloud security architecture to scale easily has caused the development of big data cloud computers to frustrate. Traditional encryption solutions require HSM (hardware) units. Needless to say, hardware deployment cannot be automated.

In order to automate the cloud security strategy as much as possible, users should choose virtual tool solutions instead of hardware solutions. Users need to understand that available APIs (*** are idle APIs) are also part of the cloud security solution. Virtual tools plus idle APIs can provide the flexibility and automation needed in cloud big data use cases.

4. Never compromise on data security

Although cloud security is usually very complicated, users will still find some "security shortcuts" in the deployment of big data. These "safe shortcuts" often seem to be able to circumvent some complex settings while keeping the big data structure "unharmed."

Some customers may use free encryption tools and store the key on the hard disk (this is very insecure and may cause the encrypted data to be exposed to anyone with access to the virtual hard disk), and some customers do not even use encryption Measures. These shortcuts are certainly not complicated, but obviously, they are not safe.

When it comes to big data security, users should classify the data according to the sensitivity of the data, and then take corresponding protective measures against them. In some cases, the results are often dramatic. Not all big data infrastructures are secure. If the data at risk is very sensitive or is regulated data, users may need to find alternatives.

Cloud security strategy for big data

Only when the most stringent security standards are established for data can big data continue to enjoy the scalability, flexibility, and automation provided by cloud computing. Encryption is considered the first step to protect cloud (big) data. New technologies such as split-key encryption and homomorphic key management should be invested in protecting sensitive data. At the same time, users also need to strictly abide by HIPAA, PCI and other regulations.