An enterprise’s inability to detect cyber attacks has tangible effects on its productivity and profitability. Various reports have noted a correlation between the time it takes to spot an intrusion and the cost of recovery.
False Positive Alerts
The fundamental SIEM flaws lie in the platform’s need for continual adjustment, endless data stores, and a tendency to create an overwhelming number of false positives. When organizations instead turn to a next-generation cybersecurity solution, which predicts behavior with an unsupervised (zero tuning) system, they are poised to save on both financial and human resources.
When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats is a bottleneck process that is setting security teams up for failure, especially with tools like SIEM, NDR, and NTA.
The world’s reliance on fast, reliable, secure networks has likely never been as apparent as it became in early 2020, when the world responded to the Coronavirus pandemic. Suddenly, vast swaths of the global workforce needed to access and send enormous stores of data from home. In some ways, it couldn’t have happened at a worse time.
MSSPs are helping their customers deal with a fast-paced and ever-evolving threat landscape. It is critical, now more than ever, to evaluate new monitoring tools that produce more actionable data and alerts to help unearth and combat these modern threats more efficiently. I recently read an article titled “4 Technologies SMBs Can Use to Modernize …