Big Data era Cloud security 4 strategy

　　

The combination of cloud computing and big data can be said to be a match. Big Data requires a flexible computing environment, which can be quickly and automatically scaled to support massive data and infrastructure. But whenever we talk about cloud computing, we can't avoid the following issues:

What is the cloud security strategy for big data?

When we mention cloud security policies in big data use cases, we want any security solution to provide the same flexibility as the cloud without compromising deployment security. When moving big data to the cloud, the following four tips allow users to enjoy both the flexibility of cloud computing and the rigorous cloud security policies they are able to achieve.

1. Encrypt sensitive data (highly recommended)

Data encryption will build 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 a cloud-big data environment. There are also solutions (such as encrypting data by a cloud service provider) that force end users to trust those who have keys, which are inherently dangerous and vulnerable.

Recent encryption techniques, such as split-key encryption, are ideal for cloud computing. While enjoying the benefits of infrastructure cloud solutions, users can keep their keys in their hands and keep their keys in a secure state. In order to get the best encryption solution for your big Data environment, we recommend using split key encryption.

2. Find cloud security solutions that can be expanded on the fabric

In big data, every component of a structure should be extensible, and cloud security solutions are no exception. When choosing a cloud security solution, users need to make sure that they work in all cross-region cloud deployment points. In addition, they must be able to scale effectively in the big data infrastructure. On the surface, this does not involve hardware problems. However, because hardware security modules (HSM) are not scalable and cannot be flexibly adapted to cloud mode, they are not suitable for big data use cases.

For the necessary extensibility, it is recommended to use cloud security solutions designed specifically for cloud computing, where security can be equivalent (or even more than) a hardware-based solution.

3, to achieve the maximum degree of automation

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

In order for the cloud security policy to be as automated as possible, users should choose a virtual tooling solution rather than a hardware solution. Users need to understand that the available APIs (preferably idle APIs) are also part of the cloud security solution. Virtual Tools plus idle APIs provide the flexibility and automation needed in cloud big data use cases. The multi-backup of the wood wave technology, as a domestic SaaS backup application, can be called the originator in this respect. Its humanized operation, simple and easy to use operation mode so that many ' small white ' users applauded. Fast backup to multiple clouds, the need for one-click Recovery is a full embodiment of automation.

4. Never compromise on data security

While cloud security is often complex, users will find some "security shortcuts" in Big Data deployments. These "security shortcuts" often seem to be able to circumvent some of the complex settings while keeping the big data structures "harmless".

Some customers may use the Free encryption tool and store the key on the hard drive (this is very insecure and may cause encrypted data to be exposed to anyone who has access to the virtual hard disk), and some customers do not even take encryption measures. These shortcuts are certainly not complicated, but it is clear that they are not safe.

When it comes to big data security, users should classify them according to the sensitivity of the data, and then take appropriate measures to protect them. In some cases, the results are often dramatic. Not all big data infrastructures are secure, and users may need to look for alternatives if the data at risk is very sensitive or is part of the regulatory data. Multi-Backup in the user backup data automatically encrypted data compression and upload to multiple cloud platforms, the use of 3-layer encryption security system to achieve the highest data security.

Summarize

Big data can continue to enjoy the scalability, flexibility, and automation provided by cloud computing, only by establishing the strictest security standards for data. Encryption is considered the first step in protecting Cloud (large) data. New technologies such as split-key encryption and homomorphic Key management should be put into the protection of sensitive data, while users need to comply with HIPAA and PCI rules.

Big Data era Cloud security 4 strategy