In the report, 451 Research explains why security analytics needs to include advanced Third-Wave AI, which autonomously learns normal behavior and adapts to constantly changing network environments, to address the next generation of cyberthreats and increase SOC productivity.
It’s no surprise that organizations are pouring resources into their security approaches, from investments into hardware and software and significant increases in Cybersecurity professional hiring. In fact, industry watchers expect organizations globally to contribute to $1.75 trillion in cumulative spending on Cybersecurity between 2021 and 2025.
Monthly reports that lack relevant details about an organization’s true risk level are insufficient and not representative of the further steps an organization should take to protect itself. This approach leaves organizations feeling secure against the threat of ransomware while they are actually left exposed to potentially expensive, wide-scale damage.
Anomaly detection, the “identification of rare occurrences, items, or events of concern due to their differing characteristics from the majority of the processed data,” allows organizations to track “security errors, structural defects and even bank fraud,” according to DeepAI and described in three main forms of anomaly detection as: unsupervised, supervised and semi-supervised. Security Operations Center (SOC) analysts use each of these approaches to varying degrees of effectiveness in Cybersecurity applications.
2020 will be remembered most as the year the world was swept up in the COVID pandemic. Dig a little deeper and you’ll find another alarming news story: 2020 was a record breaking year on the Cybersecurity front. There was more data lost in breaches and a higher number of cyber attacks than ever before.