4 Posts

Moazzam Khan

Watson for Cybersecurity Researcher

Moazzam khan has been a security researcher with Watson for Cyber Security group. His research interests involve big data analytics, security intelligence, machine learning. He has authored several collections on recent threats on IBM's threat intelligence platform XFE. Prior to joining Watson for cyber security group Moazzam had worked with L3 engineering team with GX and XGS suite of intrusion prevention systems, Proventia M series and Enterprise Scanner. Moazzam holds a doctorate from Georgia Institute of Technologies in Electrical and Computer Engineering and teaches network communication, security and data science courses as adjunct faculty.

Written By Moazzam Khan

Machine Learning Algorithms Are Not One-Size-Fits-All

Before you can choose the right machine learning algorithms to serve your business' needs, you must understand the type of problem you're trying to solve and the type of training data you'll need.

How to Choose the Right Artificial Intelligence Solution for Your Security Problems

If you're thinking about adopting artificial intelligence as an ally in your security operations center, the following questions and considerations can be helpful to guide your decision-making.

How Can Companies Defend Against Adversarial Machine Learning Attacks in the Age of AI?

Machine learning can strengthen your security posture, but it's not without its blind spots. What do adversarial machine learning attacks look like, and how can companies stop them?

Security Analysts Are Overworked, Understaffed and Overwhelmed — Here’s How AI Can Help

Today's security teams lack the time, talent and resources to keep up with the rapidly evolving threat landscape. AI can automate tedious processes and take some pressure off security analysts.