BlogThere's no denying that skilled people will always be an integral part of cybersecurity operations. After all, every cybersecurity threat requires a conversation around it, intelligent intervention, and thorough analysis to combat future issues.
Yet without the right resources at their fingertips, even the most knowledgeable cybersecurity workforce is set up to fail. Consider this in the context of a misconfiguration in the cloud—one of the top cloud security threats. If this issue is buried beneath a pile of other threats and alerts or SecOps need days or maybe even weeks to identify the root of the problem, cyberattackers have more room to make their way in the perimeter and exfiltrate sensitive data. (This year's Capital One data breach is a prime example.)
As the complexity of cybersecurity changes, so do the technologies that support it. Now, more and more cloud security tools are using machine learning to help SecOps work smarter and faster.
How Machine Learning Tools Complement a Cybersecurity Workforce
From mobile to desktop interactions, cybercriminals can launch thousands of digital attacks designed to compromise an organization's operations at every turn. Because these threats come in all shapes and sizes, it's easy for security teams to get caught up in the noise of firing alerts and let minor threats (or even false-positives) take center stage while more inconspicuous but devastating threats, like insecure APIs or misconfigured identity and access systems, fall under the radar.
Rather than have to manually filter through potential threats and lose precious time in the process, a cybersecurity workforce can lean on machine learning algorithms to guide their investigation. With advanced behavioral analytics, these algorithms simplify the detection of both known and unknown threats—all while extracting patterns from the data it collects for even better accuracy and to simplify future threat hunting.
(Tip: While machine learning models do require a lot of computational resources and storage power to process large volumes of data, this doesn't have to be a burden to on-premise appliances. Choosing cloud-scale machine learning moves these compute-intensive workloads to the cloud for nearly unlimited compute and storage power. This allows organizations to train and execute ML models in their hybrid environment in a highly scalable way.)
Applying machine learning to network data (the purest form of truth) delivers complete visibility of the east-west traffic—what's considered a dark space in security environments as log- and agent-based monitoring tools focus solely on north-south traffic—enables SecOps to shine a light on every conversation between their systems and devices. So when (not if) an attacker breaks in, SecOps will not only be alerted of the incident; they'll be able to anticipate the intruder's next move and immediately contain and remediate the threat.
For those businesses already operating in hybrid environments, improved east-west visibility helps to diffuse threats faster and minimize risks, while allowing cybersecurity professionals to attend to other matters. For businesses that are migrating to the cloud, the benefits are twofold: SecOps will have an accurate baseline of their applications and services performance before, during, and after migration, with an improved security posture once the transition is complete.
ExtraHop's architecture uses a unique combination of on-premises technology and cloud services to support the full machine-learning process while protecting the confidentiality, integrity, privacy, and anonymity of customer data and activities. While our machine learning service is based in ExtraHop's cloud in order to scale effortlessly with your enterprise, only de-identified metadata is sent to the cloud. Data categories containing potentially sensitive information such as payloads, filenames, or strings will remain on your premises, and we obtain SOC 2, Type 1 compliance certification for our machine learning service every year.
Whether you want to see our product's capabilities in the scope of a live attack, data exfiltration or simply explore the software, try our interactive demo.
