Every year the protection of private and confidential information gains more and more attention. According to the World Quality Report 2015-16, the only global report for application quality, security is the most highly ranked priority in the IT strategies used by survey respondents.

Until recently, a company’s applications were mainly internal and its security was viewed as low risk. However, with the increased adoption of web-based, mobile and cloud-based applications, sensitive data has become accessible from different platforms. These platforms are highly vulnerable to hacking, especially if they are low-cost or free.

Nowadays, organizations are collecting and processing massive amounts of information. The more data is stored, the more vital it is to ensure its security. A lack of data security can lead to great financial losses and reputational damage for a company. As far as Big Data is concerned, losses due to poor IT security can exceed even the worst expectations.

What are the Main Challenges When it Comes to Big Data Security?

Almost all data security issues are caused by the lack of effective measures provided by antivirus software and firewalls. These systems were developed to protect the limited scope of information stored on the hard disk, but Big Data goes beyond hard disks and isolated systems.

Nine Big Data Security Challenges

1. Most distributed systems’ computations have only a single level of protection, which is not recommended.
2. Non-relational databases (NoSQL) are actively evolving, making it difficult for security solutions to keep up with demand.
3. Automated data transfer requires additional security measures, which are often not available.
4. When a system receives a large amount of information, it should be validated to remain trustworthy and accurate; this practice doesn’t always occur, however.
5. Unethical IT specialists practicing information mining can gather personal data without asking users for permission or notifying them.
6. Access control encryption and connections security can become dated and inaccessible to the IT specialists who rely on it.
7. Some organizations cannot – or do not – institute access controls to divide the level of confidentiality within the company.
8. Recommended detailed audits are not routinely performed on Big Data due to the huge amount of information involved.
9. Due to the size of Big Data, its origins are not consistently monitored and tracked.

How Can Big Data Security be Improved?

Cloud computing experts believe that the most reasonable way to improve the security of Big Data is through the continual expansion of the antivirus industry. A multitude of antivirus vendors, offering a variety of solutions, provides a better defense against Big Data security threats.

Refreshingly, the antivirus industry is often touted for its openness. Antivirus software providers freely exchange information about current Big Data security threats, and industry leaders often work together to cope with new malicious software attacks, providing maximum gains in Big Data security.

Here are some additional recommendations to strengthen Big Data security:

• Focus on application security, rather than device security.
• Isolate devices and servers containing critical data.
• Introduce real-time security information and event management.
• Provide reactive and proactive protection.

What’s Next for Big Data Security?

Of immediate concern to companies using Big Data is the security of cloud-based systems. Intel Security has recently published the McAfee Labs’ Threat Predictions Report that contains their expectations for the near-future of data security. Of particular concern in this report is the supposition that legitimate cloud file hosting services such as Dropbox, Box, and Stream Nation, are at risk of being used as control servers in upcoming cyber espionage campaigns. If targeted, these popular cloud services could enable the malware to transfer commands without raising suspicion.

Malicious attacks on IT systems are becoming more complex and new malware is constantly being developed. Unfortunately, companies that work with Big Data face these issues on a daily basis. Nevertheless, every problem has a solution and finding an effective and suitable answer for your organization is indeed possible.

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Article was originally published on Data Center Knowledge.