Prevenindo ameaças persistentes avançadas em redes corporativas utilizando um modelo de segurança baseado em zero trust e UEBA
Não consta.
Many organizations are being targeted by various types of attacks. One of the most dangerous attacks is called Advanced Persistent Threats (APT) as it is silent and it’s main goal is spying and stealing information, different from a denial of service (DoS) attack, por example. The proposed solution addresses the implementation of a security model based on zero trust in conjunction with UEBA to profile user behavior and find anomalous behaviors of adversaries in order to prevent APT attacks on corporate networks. The proposal consists of using machine learning concepts specifically within each micro-segmentation and analyzing whether there was a reduction in false negatives.