Nowadays, it’d be pretty difficult to find an enterprise that doesn’t use big data in some capacity for its daily operations. That’s the nature of big data — it’s versatile (as well as a few other V-words, but more on that in a minute) and helps companies distinguish new opportunities, inform business decisions and strategies, improve consumer experiences and boost efficiency. Because big data is so useful and encompasses so much, it’s often the target of security threats.
What is big data?
In order to understand the risks to big data and how to prevent them, you first need to know what exactly constitutes “big data.” The term itself is quite broad and not restricted to a specific type of data. Rather, data is considered “big” when it can be defined by the four V’s:
- Volume, or data that’s collected, processed and stored in large quantities.
- Velocity, or data that’s created at unparalleled rates and must be handled in just as timely a manner.
- Variety, or data that’s gathered in all sorts of structured and unstructured formats. Depending on the type of business, this can include emails, photos, videos, audio recordings and social media details, as well as personally identifiable information (PII), which is why cyberattackers want to get ahold of it.
- Veracity, or data that’s accurate and can in turn be used by enterprises to make informed business decisions.
What is big data security?
In short, big data security is the process of implementing safeguards to protect an enterprise’s big data from unauthorized access or breaches throughout the entirety of its lifecycle. During its lifecycle, data can live in cloud repositories as well as physical locations like endpoints and hardware storage devices. Your protection plan must take into account the security risks posed to all of these locations.
Big data security risks
Namely, these security risks include:
- Third-party applications
- Endpoint devices
It’s not uncommon for enterprises to employ third-party applications, such as payroll and benefits software or email marketing automation tools, to carry out specific business functions. These applications must process sensitive data in order to execute their tasks, but without security protocols in place that are up to par with those of the enterprise, the enterprise’s data is at risk for compromise.
To reduce this risk, enterprise organizations should consider creating contracts between themselves (the data controllers) and any third-party applications that will process their sensitive data to detail security measures and specific responsibilities, and ultimately, get all parties on the same page.
Endpoint devices such as desktop or laptop computers, smartphones, tablets and servers pose risks to big data security, especially as remote work increasingly becomes the norm. Without the protection of an enterprise’s secure network, cyberattackers can readily compromise an endpoint device using phishing scams, ransomware or eavesdropping attacks to gain access to sensitive data.
In order to combat this, enterprises must secure all endpoints capable of accessing their servers with measures like firewalls, encryption and threat intelligence software. Additionally, employees should be required to use a virtual private network (VPN) when working remotely to safely access an enterprise network.
But, even with all these safeguards in place, breakthrough cyberattacks are highly possible. By the time you’re notified of a compromise, the cyberattacker is already in your environment. To ensure your sensitive data is actively protected at its source, IT security teams need to secure endpoint devices with a sensitive data discovery tool that accurately locates sensitive data anywhere it exists across those endpoints and immediately protects it.
Not all enterprises are as strict as they should be when it comes to limiting sensitive data access to authorized personnel only. Because of this, users can jeopardize security by intentionally misusing sensitive information or inadvertently exposing it and leaving it vulnerable to an attack. Implementing tighter controls that govern who can access what data and how it’s used can significantly reduce this risk.
Protecting big data from security threats
The solution to protecting your organization’s big data from these risks and beyond starts with accurate sensitive data discovery. Once you know what exists and where, as well as how it could be threatened, you’re in a much better position to begin securing it.
Your actual security strategy will depend on how your organization’s data is classified. When you’re able to see your data broken down by sensitivity, you’ll understand the different levels of protection needed to keep it safe and in turn make informed decisions regarding the measures you implement, like user access controls and encryption.
Constant remediation is the final step in protecting your organization’s big data. Because of the amount of information being created and collected within your enterprise, as well as the variety of it, there’s an increased risk of abnormalities, inconsistencies and duplicates developing that could go unnoticed. Remediation keeps these in check to reduce your data’s footprint and boost its veracity for efficient business use.
Secure big data with Spirion
Think of your enterprise’s digital infrastructure as a closet and its big data as items — both junk and valuable — messily strewn about. This metaphorical closet can get so inundated and disorganized that if someone were to break in and steal from it, you wouldn’t even know what was missing. The ideal solution to get organized would regularly and automatically show you what valuable items you have so they can be properly stored and protected. It would also show you what junk you’ve got — unnecessary duplicates and items that don’t fit or aren’t useful anymore — so you can dispose of them accordingly.
Spirion’s Sensitive Data Platform is that solution, but for your big data. It automatically discovers sensitive data wherever it lives within your organization (including those risky endpoint devices) so it can be strategically secured, persistently classifies it — which is essential for processing big data at the volumes and velocity that it’s created — and remediates it to ensure it’s as accurate and valuable as possible to fulfill business needs. To learn more, contact us today.