{"id":23899,"date":"2022-12-16T01:48:33","date_gmt":"2022-12-16T01:48:33","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/16\/making-medical-iot-devices-more-secure-with-machine-and-deep-learning\/"},"modified":"2022-12-16T01:48:33","modified_gmt":"2022-12-16T01:48:33","slug":"making-medical-iot-devices-more-secure-with-machine-and-deep-learning","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/16\/making-medical-iot-devices-more-secure-with-machine-and-deep-learning\/","title":{"rendered":"Making medical IoT devices more secure with machine and deep learning"},"content":{"rendered":"

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Even though smart medical devices are providing breakthrough improvements and reimagining patient experience, they open up vulnerabilities to new attacks and exploits that can disrupt hospital operations and put patients in danger.<\/p>\n

With a 200% increase in cyberattacks in healthcare organizations and connected devices expected to hit 1.3 billion in this field, Palo Alto Networks Inc. changes the narrative of medical devices being the weakest link on the hospital network through machine learning, segmentation and deep learning, according to Anand Oswal<\/a> (pictured), senior vice president and general manager of product at Palo Alto.<\/p>\n

\u201cThrough a lot of innovation that we\u2019ve done in both machine learning and\u00a0deep\u00a0learning to be able to look at unstructured data and\u00a0be able to stop the attacks in-line in real time, you need to use machine learning to identify what these devices are, what\u2019s the unpatched vulnerabilities,\u201d\u00a0Oswal stated. \u201cThen you need do segmentation \u2026 about who can talk to whom. Should your CT\u00a0scan machine or MRI\u00a0machine be talking to a server in the corporate environment or to your point of sale terminal in the hospital?\u201d<\/p>\n

Oswal spoke with theCUBE industry analysts\u00a0Lisa Martin<\/a>\u00a0and\u00a0Dave Vellante<\/a>\u00a0at\u00a0Ignite \u201922<\/a>, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed how Palo Alto is helping to secure the healthcare sector through cutting-edge technologies such as machine and deep learning. (* Disclosure below.)<\/em><\/p>\n

Stopping attacks in real time<\/h3>\n

Since attackers are using more sophisticated methods to evade traditional sandboxing techniques, Oswal believes machine learning comes in handy in averting threats in real time. This is based on the repetitive nature of malware.<\/p>\n

\u201cNinety-five percent of all malware in the world is more of malware,\u00a0which means it\u2019s variations of existing malware,\u201d he pointed out. \u201cWe invested a lot in machine learning and\u00a0deep\u00a0learning\u00a0to stop these day-zero threats in-line in real time. Attackers are using that window of opportunity so you have to out-innovate them.\u201d<\/p>\n

Revamping legacy networks in the healthcare sector is crucial for enhanced security. Moreover, the zero-trust policy should be incorporated, according to Oswal.<\/p>\n

\u201cMajority\u00a0of healthcare organizations have legacy security architectures,\u201d he said. \u201cYou need to get fully integrated, because you need to\u00a0reduce their operational costs. You need to ensure that they have better security. You wanna have least privilege access.\u201d<\/p>\n

Here\u2019s the complete video interview, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of\u00a0Ignite \u201922<\/a>:<\/p>\n