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A lack of AI-based security and
inefficient protocols make IoT
healthcare devices vulnerable to
cyberattacks, says report

Lack of AI security puts IoT medical devices in danger of cyberattacks

by John R. Fischer , Staff Reporter
A lack of AI-based security tools and inefficient protocols by staff have made healthcare internet-of-things (IoT) devices easy targets for cybercriminals, according to the Vectra 2019 Spotlight Report on Healthcare.

The provider of AI detection tools for cybersecurity threats asserts in its findings that insufficient access controls, reliance on legacy systems and unpartitioned networks have left medical IoT devices vulnerable to hacking that could result in the theft of personally identifiable information (PII) and protected health information (PHI), as well as disrupt healthcare delivery processes. The report suggests that such risks could be mitigated with the inclusion of AI for detecting hidden threats in enterprise IT networks.

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“Healthcare organizations struggle with managing legacy systems and medical devices that traditionally have weak security controls, yet both provide critical access to patient health information,” said Chris Morales, head of security analytics at Vectra, in a statement. “Improving visibility into network behavior enables healthcare organizations to manage risk of legacy systems and new technology they embrace."

Policies and procedures that are not thorough and lack essential details can lead staff members to commit errors such as improper handling and storage of patient files, which cybercriminals can target and exploit as a weakness.

Utilizing Vectra’s Cognito threat-detection and response platform, the authors of the report assessed the actions and trends in networks from a sample of 354 opt-in enterprise organizations in healthcare, as well as eight other industries. The platform utilizes AI to collect, enrich and store network metadata with the right context to detect, hunt and investigate hidden threats in real time. It can scale to the largest organization’s networks with a distributed architecture made up of a physical, virtual and cloud sensors that prevent attackers from hiding by providing 360-degree visibility across cloud, data center, and user and IoT networks.

Based on network traffic monitoring and metadata of more than three million workloads and devices, they found that attackers blend with existing network traffic behaviors to hide their intentions and carry out a number of approaches that set off risks for businesses and disastrous data breaches.

They include:

• Using hidden Hypertext Transfer Protocol Secure (HTTPS) tunnels to high command-and-control communications in healthcare networks. This enables external communication of information in multiple sessions for long periods of time that appears to be normal encrypted web traffic.
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