Virtual Assistant Chatbots are becoming a vital part of every company's technology infrastructure.
Are you protecting yours?
Machine Learning attacks are the next major threat vector in the security world. How well we protect against them will determine how widely and confidently we can deploy A.I.
Virtual Assistant Chatbots are vulnerable to a new type of attack made at the machine learning level. As the machine learning models used by these systems are built with open source algorithms, trained with internally and externally sourced datasets and then improved over time with additional incoming data, there are new vulnerabilities inherent in the technology that are now beginning to be exploited. Add to this the fact that the vehicle used to attack the system is the very text conversation that is the foundation of the technology and it is clear that these new security threats need to be proactively addressed.
Attacks on Virtual Assistant Chatbots are specifically difficult to defend against because nothing is currently done to analyze the context of the conversation between the user and the system so companies are blind to malicious actions. Not only is this dangerous because companies miss new external attacks, but even worse is the fact that hacked responses coming out from the system to users are trusted by both the company and also the user. Both company and user implicitly trust the output from the system making a hacked Virtual Assistant Chatbot the perfect vehicle for attacks.
You need a security solution that is intelligent enough to separate legitimate conversations from malicious actions. This requires a company with a deep understanding of AI, machine learning, natural language processing and data science. Scanta combines these skills to create a new level of security empowered to stop machine learning attacks on Virtual Assistant Chatbots by analyzing context at the conversational level.
VA Shield™ helps businesses protect their Virtual Assistant Chatbots from machine learning attacks to keep them running continuously, safely and securely without disrupting existing security workflows.