Taxonomy of AISecOps Threat Modeling for Cloud Based Medical Chatbots
Ruby Annette J, Aisha Banu, Sharon Priya S, Subash Chandran

TL;DR
This paper develops a taxonomy for AISecOps threat modeling tailored to cloud-based medical chatbots, integrating security, AI, and cloud operations to enhance threat detection and protection.
Contribution
It applies the STRIDE threat modeling framework specifically to medical chatbots, enabling automatic threat detection and addressing security concerns in sensitive data environments.
Findings
Tailored threat modeling framework for medical chatbots.
Potential for automatic threat detection using AISecOps.
Applicable to other sectors like finance and government.
Abstract
Artificial Intelligence (AI) is playing a vital role in all aspects of technology including cyber security. Application of Conversational AI like the chatbots are also becoming very popular in the medical field to provide timely and immediate medical assistance to patients in need. As medical chatbots deal with a lot of sensitive information, the security of these chatbots is crucial. To secure the confidentiality, integrity, and availability of cloud-hosted assets like these, medical chatbots can be monitored using AISecOps (Artificial Intelligence for Secure IT Operations). AISecOPs is an emerging field that integrates three different but interrelated domains like the IT operation, AI, and security as one domain, where the expertise from all these three domains are used cohesively to secure the cyber assets. It considers cloud operations and security in a holistic framework to collect…
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Taxonomy
TopicsBlockchain Technology Applications and Security
