Scope of LLMs and GPT Models in Security Domain


In today’s digital world, we have access to everything at our fingertips. We generate and consume data at a lightning speed. Data is growing at an exponential rate. But how safe is your data? Our data is always surrounded by advanced persistent threats (APTs). On the other hand, Data Science, Machine Learning & Artificial Intelligence (AI) with its sub-domains like Deep Learning and Large Language Models (LLMs) are making tremendous progress. In this talk, I will focus on the advanced technologies like LLMs and GPT models in the domain of cyber security. But some of these concepts are relatable to other industries as well.

I have been working in the intersection of Data Science and Cyber Security for a long time. However, I still pause and ponder- where is that perfect intersection of Data Science and Security? How does current advancement of generative AI models like chat-GPT and other LLMs can help the Security Analysts to do their job more effectively and efficiently? What are the new skills to learn for someone who wants to enter the career path of AI in Cyber Security? While this has been the hot topic of the market, there are still many challenges when it comes to applying advanced ML to cyber security. Besides the challenges, risks and data privacy on one side, there are more opportunities now than ever. Generative AI has opened up new doors for every industry, not only for cyber security.

Interestingly enough, cyber security is very closely aligned with warfare. Adversaries are not governed by any rules or laws when they are attacking, while we have to follow many policies and laws before we can have our defensive systems in place.

In this talk, I will be covering some real-world use cases, and case studies on opportunities and challenges when it comes to big data, machine learning, and Generative AI in the field of cyber industry.

Learning objectives for audience attending this talk are:

· How data science intersects with cyber security

· What are top skills to develop if you want to work in this rare intersection

· Generative AI in security- Adversaries are already using it ahead of us

· Real world use cases on opportunities vs. challenges of LLMs in security


Nirmal Budhathoki is a Senior Data Scientist, who is currently working at Microsoft in Cloud Security. Nirmal has over 12+ years of experience in the IT industry, including 5+ years in data science. Nirmal’s strong belief in continuous learning has led him to complete three master's degrees with majors on: Information Systems, Business Administration, and Data Science. Nirmal loves to help the data science community and has completed over 600+ free mentoring sessions with aspiring data scientists to help them navigate their data science career. Nirmal also conducts mentored learning sessions for MiT’s Data Science and Machine Learning certification program in collaboration with Great Learning. Nirmal has experience working with the US government for the Department of Navy, and he is also a US army veteran. Nirmal yearns to solve data science problems that are aligned with product strategy and business outcomes. In his free time, Nirmal loves using this data science skills in sports analytics.

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