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IBM Watson Launches Healthcare AI Cybersecurity Beta Program

IBM Watson for Cyber Security Beta Program enlists 40 organizations to test and develop a cognitive cybersecurity solution for more accurate threat assessments.

IBM has launched the IBM Watson for Cyber Security Beta Program with 40 organizations in industries including healthcare, insurance, and education.

IBM Watson AI cyber security

IBM Watson for Cyber Security program intends to address the security challenges organizations face as IT infrastructures grow more advanced. Advanced technological environments drive the need for an intelligent means of identifying and prioritizing cyber threats.

Watson for Cyber Security uses machine learning and natural language processing to assist IT professionals in making well-informed and timely decisions based on large amounts of structured and unstructured data.

"Customers are in the early stages of implementing cognitive security technologies," said Sandy Bird, Chief Technology Officer, IBM Security. "Our research suggests this adoption will increase threefold over the next three years, as tools like Watson for Cyber Security mature and become pervasive in security operations centers. Currently, only seven percent of security professionals claim to be using cognitive solutions."

The organizations currently participating in the beta program are leveraging Watson to build an intelligent security solution to give them better insight to determine suspicious behavior. Watson provides additional context for user activity outside of the most common suspicious behavior, which aid IT staff in determining whether certain behavior is malicious.

Watson for Cyber Security also checks suspicious activity against known malware or cyber crime campaigns to provide IT staff with background and inform more accurate decisions based on known characteristics of malware.

The organizations participating in the beta program will play a key role in the development of the final product. IBM intends to tailor their cognitive cybersecurity solutions to meet specific needs require by different industries and apply them to other areas of their security portfolio.

Other areas set to find improvement through current testing include applying behavioral analytics to better understand the usage patterns in insiders for IBM QRadar User Behavior Analytics and visualizing data access in a single 3D view empowers security teams to detect and flag suspicious activities before they turn into a breach, using IBM Security Guardium.

Security professionals expect to see improved detection and incident response decision-making capabilities from the cognitive security technology. Security professionals are finding it difficult to make the most accurate threat assessments with the amount of data brought in using just traditional cyber security methods.

A recent report released by Grand View Research pegs encryption to be the future of healthcare cybersecurity in order to keep advancing technology safe from evolving threats.

Encryption is a necessary technology for all secure health IT infrastructure environments; however, encryption is more of a reactive technology and does not possess the potential proactive response of a cognitive cybersecurity solution.

Healthcare organizations are trying to keep up with the evolving cloud, IoT, and artificial intelligence solutions as well as protect their networks from threats which have evolved along with healthcare technology to take advantage of digital environments.

The healthcare industry is seeing spikes in cognitive and artificial intelligence solutions most prominently in the big data and analytics space, but Watson for Cyber Security could potentially bring a new use for artificial intelligence in the healthcare industry.

The University of Rochester Medical Center is one of the 40 organizations currently participating in the Watson for Cyber Security Beta Program. The organization has been using IBM Watson to advance their care and research since 2013.

Healthcare organizations currently using IBM Watson for other initiatives may benefit from the results of the beta program and be able to implement machine learning techniques to their security measures to better protect clinical data in the future.

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