In recent years, you’ve likely seen cybersecurity companies tossing around buzzwords related to machine learning, artificial intelligence, and data science with increasing frequency, and for good reason. ML models, if designed with care, can provide solutions to problems that are too complex or time consuming for humans alone. They can speed up processes and augment products in impressive ways. Unfortunately many organizations miss the mark, attracted by the buzzword but lacking the experience, intention, or understanding to generate high value with machine learning. The simple fact is that ML sells, even if an organization’s use of ML isn’t elevating their product or, in a worst case scenario, is creating dangerous blind spots. As a seasoned data scientist who’s passionate about building ML models for information security, this drives me crazy.
In this talk, I will break down the information asymmetry that exists between ML theory and its real time applications in the cybersecurity world. I’ll talk about precautions necessary when using traditional ML models for cyber-security, and how to protect ML models themselves from adversarial attacks.
If you’re considering how to implement ML in your product, curious if the data scientists within your organization are spending their days building meaningful models or not, are looking for ways to weed through the buzzwords when vetting a new security product, or are somewhere in between, join me to learn how to generate high value with machine learning.
Dr. Deepali Arora is an experienced data scientist with a proven track record of developing AI based models for deriving actionable insights for various industrial applications. Over the course of her rich career as a data scientist, Dr. Arora has developed models for companies operating in the following domains: telecommunications and Internet of things (IoT), security of computer systems and cloud infrastructure, healthcare, eCommerce, gaming, mining, social media, travel sector, and online real time targeted mobile advertising. Some of the AI based models developed by Dr. Arora are still used across companies with strong presence in Canadian or Global markets and has helped those companies in saving thousands of dollars in resources. Dr. Arora obtained her Ph.D degree from the department of Electrical and Computer Engineering, University of Victoria and has published nearly 33 papers in top tier journals and conference proceedings. She also serves as an advisor for couple of AI based start-up companies and is an active speaker focussed on promoting meaningful data science applications at various industrial events and conferences.
Dr. Arora is currently working as a Manager Data Science and Analytics, for Cmd, a proactive Linux security company that is building a software to protect sensitive data of some of the world’s top enterprise organizations from potential security breaches.
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