The occurrence of cyberattacks on businesses of all sizes keeps rising. In fact, it’s estimated that more than three-fourths of U.S. businesses (76 percent) have experienced one within the past year. And while huge enterprises at definitely at risk for exploitation by hackers; small- and medium-sized businesses are experiencing their fair share of attempted and successful attacks, too. Consequences range from compromised data to damaged customer trust, costly business downtime in the wake of the attack and possible regulatory penalties.
Businesses are also able to collect, store and analyze more data than ever before — which is something of a double-edged sword. It’s beneficial for a company to have more data at its disposal to utilize when making decisions and optimizing performance. But it means enterprises are responsible for safeguarding more information from hackers, too. There’s more pressure than ever before to protect data assets by closing IT gaps and defending a growing number of devices on the network.
The good news is enterprises can actually harness data to improve cybersecurity.
What Data Adds to Cybersecurity
Cybersecurity has many components whether companies handle their IT endeavors in house or outsource them to a third-party security-as-a-Service (SECaaS) vendor. Even with these cybersecurity measures in place, companies still face the challenge of detecting threats and resolving them as speedily as possible to block or minimize their ill effects.
This is where data comes in. According to Digitalist Magazine, analytics tools can:
- Detect emerging cybersecurity threats like malware and ransomware
- Identify devices on the network that contain weaknesses or have been compromised
- Uncover harmful insider programs that have been introduced to the network
Artificial intelligence and machine learning algorithms — powered by data analytics — can quickly and constantly scan networks for anomalies, patterns and potential risk factors. They can then swiftly flag IT specialists who will investigate the issue and take the required action
As ISACA outlines, companies that have already suffered one or more cyberattacks in the past can use data from around the time of the attacks to identify patterns that might reveal how the hackers gained entry into the network. Learning from them can minimize the possibility of a successful repeat incident.
Challenges Companies Face in Harnessing Data
The fact that so much data exists today can be an advantage, but it can also leave companies swamped and unsure where to start if they lack the tools to effectively analyze it.
As more companies move toward a hybrid or cloud model of computing, their approach to software-defined wide area networking (SD-WAN) becomes make-or-break. At minimum, this tech can furnish advanced firewalls, Domain Name System filtering and secure web gateways to shut out many common cybersecurity threats. But another SD-WAN feature from SECaaS vendors like Open Systems is the ability to analyze data to detect threats in real time, then drill down to get to the bottom of any events flagged as suspicious.
If companies go the route of handling cybersecurity and data analytics in house rather than outsourcing it to a third-party vendor, they must ensure they have the tools — and the users of these tools have the training — to enact “sophisticated data analytics at scale in real time,” as CIO advises.
What does this look like in action? Human specialists — namely data analysts and scientists —work closely with AI/machine learning tools to define normal versus anomalous activity. They can then respond to threats as they’re exposed.
Eliminating cumbersome data silos is a precursor to powering rapid, enterprise-wide data analysis. Data increasingly holds the key to preventing and mitigating cyberattacks. Businesses of all sizes can benefit from auditing their approaches to data analysis and network security.