MixMode’s leadership team came together to share more on how our context-aware AI builds network baselines for organizations across the globe, it’s predictive capabilities, and how MixMode helps you more intelligently discover anomalies within your network environment.
While it’s true that having a SIEM is better than forgoing network monitoring all together, a standalone SIEM solution is simply insufficient in today’s cybersecurity landscape. Hackers and other bad actors have become more sophisticated — many of today’s cybercriminals can easily outsmart a standard SIEM setup.
The reality is that most companies and entities are entrusted with sensitive data. As regulations tighten and consumer expectations rise, it is more important than ever to protect data, whenever it is gathered, accessed, shared, or stored. Let’s take a look at a few of the newsworthy data breaches that happened in 2019. Often, studying these cases can inform SecOps teams about what not to do.
Knowing the difference between Discriminative and Generative Unsupervised Learning can tell you a lot about the effectiveness of a cybersecurity solution’s artificial intelligence, for example, whether or not that security solution can perform actions like identifying and stopping a zero-day attack.
In October, 2019 a MixMode customer experienced an incident where an external entity attacked a web server located in their DMZ, compromised it, and then pivoted internally through the DMZ to attempt access of a customer database. While the attacker was successful in penetrating the customer’s network, MixMode was able to detect the event before they were successful in penetrating the customer database.