Zero Trust Machine Learning Security Solution Considerations
Machine Learning solutions have the potential to revolutionize industries, but they also expose a new type of attack surface for cybercriminals. To secure the integrity and privacy of data and models, teams must proactively evaluate security risks and mitigations for ML solutions. Understanding the particular security problems of Machine Learning, integrating security into the development and deployment process, and staying current with the latest research and breakthroughs in ML security are all part of this. Data poisoning, model inversion, model stealing, adversarial examples, poisoned updates, and privacy leakage are some of the top security concerns for Machine Learning solutions.
