Report: A vulnerable attack surface exists in healthcare enterprise IT networks

Vectra, the leader in network threat detection and response, today announced that the proliferation of healthcare internet-of-things (IoT) devices, along with unpartitioned networks, insufficient access controls and the reliance on legacy systems, has exposed a vulnerable attack surface that can be exploited by cybercriminals determined to steal personally identifiable information (PII) and protected health information (PHI), in addition to disrupting healthcare delivery processes. Published in the Vectra 2019 Spotlight Report on Healthcare, these findings underscore the importance of utilizing machine learning and artificial intelligence (AI) to detect hidden threat behaviors in enterprise IT networks before cybercriminals have a chance to spy, spread and steal. Machine learning and AI can assist healthcare organizations in better securing networks, workloads and devices, and provide data security by analyzing behaviors across systems," said Jon Oltsik, senior principal analyst at Enterprise Strategy Group. According to ESG research, "12 percent of enterprise organizations have already deployed AI-based security analytics extensively, and 27 percent have deployed AI-based security analytics on a limited basis. We expect these implementation trends will continue to gain.