How to Deal with Big Data Security Issues

This is a clear era of big data, but it is not necessarily an era of ensuring big data security. The databases of some large companies have suffered terribly large-scale damage, including Home Depot, Target, NiemenMarcus, and most recently Ashley Madison. Most big data collectors do not do enough to protect their valuable information from prying eyes. Without major changes in security protocols from consumers to manufacturers to suppliers, the attractiveness of big data as a target for malicious hackers increases.


How to deal with frequent big data security issues is the key

Unfortunately, there are some issues that prevent data collectors from fully protecting their data. However, solutions to these problems can ensure a long-term case for big data in the future-as long as you and others formulate them.

Major big data security challenges

Traditional security mechanisms such as firewalls and antivirus software are currently installed on your computer, but they are not enough to protect big data. The problem is that these measures are to protect small-scale, static information files. You have a lot of information stored on your hard drive, not the terabytes of information from cloud computing. On the contrary, the security for big data must be flexible and fast, allowing fast flow and multiple entries.

Experts discovered weaknesses in the way that modern enterprises use big data in their conversations with members of the Cloud Security Alliance (a non-profit organization that is determined to improve cloud security). These measures include:

• Distributed programming framework for secure computing. A program that executes multiple calculation stages must have multiple protections: one for the program, and one to protect the data in the program.

• Security of non-relational data storage. Also known as NoSQL, non-relational storage continues to evolve, and when they do, proper security must mature along with them.

• Secure data storage. In the past, IT managers could directly control when data moved between tiers, but it was difficult to directly control big data. The automatic layering requires additional security mechanisms.

• Endpoint input verification. When a system receives millions of input data, it is usually done as big data collection. It is necessary to ensure that each input data is credible and valid.

• Real-time security monitoring. So far, real-time security is not excellent at identifying real security threats, and thousands of false information are generated every day.

• Analysis of data mining and privacy protection. Big data is only one step away from true and private data, because it can edit strong private information without consumers' awareness or consent.

• Encrypted access control and secure communication. For complete security, the data must be encrypted end-to-end, but it must also be valid and available to those who need it.

• Fine-grained access control. Not all data is equally confidential. Companies should be able to filter their security and share as much as possible while keeping the most sensitive information safe.

• Scalable auditing. To learn about security violations, there must be detailed audits available for review; however, due to the size of the big data, these reports must also be scalable to this event.

•data source. The provenance complexity of data sources continues to grow, but the source graphs analyzed have already met the requirements of computing power.

Suggestions for improving the security and effectiveness of big data

Cloud computing experts believe that the most sensible guide to the improvement of big data security is the anti-virus software industry that has decades of history. Antivirus software companies have a lot of experience in dealing with various threats. Countless anti-virus software vendors are working hard for this and have all tried to protect data from the infiltration of nasty digital errors.

However, what cloud computing experts value most in the antivirus industry is its openness to data. Instead of locking down their security secrets and gaining an advantage over competitors, anti-virus vendors (including NGOs, public institutions, and even private companies) will freely communicate and exchange threat data. Industry*** can work together to resist new and dangerous malware and ensure ubiquitous computer security. This open communication and lack of destructive competition is exactly what big data needs to build strong security quickly and efficiently.

Currently, organizations like the Cloud Security Alliance are trying to cooperate for cloud protection, but they have not yet generated enough trust to create real progress in the industry. You should support the efforts of these organizations and teams to ensure a strong future for big data.