Over the past few years, Big Data security is gaining more and more attention. As a point of fact, the World Quality Report of the past 2 years shows that security is the major concern of technical departments around the world. The reason for this is that companies have started to use a number of visible applications to manage their processes. This alone has increased security threats and big data breaches. This phenomenon also includes the unification of mobile into businesses.
Almost everyone at offices brings their mobile phones with them. Even if you are following every single security tip and are not connected to the company’s network, even though you can easily harm its security. Even the slightest mistake can cause a data breach, that also counts just plugging in your phone in PC or laptop. Even the use of third party software such as a work timer app can eventually become the reason for a data breach.
Here are some key challenges that companies face with big data security.
Table of Contents
Making data vulnerable
Hence all of your data is digitalized and is in enormous volume, hackers can always find their way inside with the help of malicious insiders. If somehow they have access to your critical data they can make amendments or even delete some of it as per their purpose. This is the reason why companies that completely rely on IoT, big data and real-time data analytics limits access and make certain steps to detect fake data formation. That is a crucial part of their data protection protocols.
Such as, a production company can get corrupted temperature reports, hence resulting in slow production and loss of revenue.
Making access difficult
Another important ingredient that makes big data ecosystem operative is granular access control. Based on ranks, authorities can grant different persons different levels of access authorities to the main data. Nominally, access controlling makes big data even more secure. However, as organizations use an enormous amount of data, increasing complex control panels can become more subtle and open a gateway to more potential vulnerabilities.
Such as, if only a few numbers of people have granted access to critical data, it is going to take longer for the breachers to notice it. Moreover, the access control system specifies the information that a user is allowed to see in data sets, even though they require other sets of data. This can compromise both the performance and the maintenance of such a system.
Require certain security audits
Security audits are almost needed at every system development, specifically where big data is disquieted. However, these security audits are often overlooked, considering that working with big data already comes with a large range of challenges, and these audits are just another thing to be added to the list. This attitude is combined with the fact that many companies still need qualified personnel who can design and implement such security audits.
Diffused frameworks
Companies that are using big data will likely require the distribution of data analytics across different systems. For instance, Hadoop is an open-source software designed for flexible and diffused computing in the big data ecosystem. However, that software originally had no security at all, hence effective security in diffused frameworks is still a challenge to achieve.
How does this affect an organization? Well, it can take longer for companies to know when a breach actually occurs.
Data roots
Finding our data origin is really helpful when it comes to identifying where a breach has come from. You can use metadata to track the flow of data. Anyhow, metadata management is a self strategic issue for even large companies. Without the right framework, tracking such unstructured data in real-time is a challenge. Though it is an ongoing problem, it isn’t a big data concern.
Real-time compliance
Big data analytics in real-time are gaining popularity among companies’ rivalry. However, implementing such a tool in real-time is even more complicated and produces an enormous amount of data.
Such tools should be developed in such a way they should be able to evade false warnings of breaches when in reality there is no such threat. So, uncovering such false warnings can be time-consuming. Eventually, they distract white hat hackers from real malfunctioning and attacks and waste resources as well.
Conclusion
Sadly, organizations that handle Big Data have to deal with such problems all around the year, without any anticipated end in sight. This never-ending fight will become more and more difficult to win. Anyhow, you can make this battle easier by making small steps to your security enhancements, amend data access and usage, and regularly monitor your traffic with real-time screen monitoring.
