Skip to main content
Microsoft Security

Microsoft Security Blog

New machine learning model sifts through the good to unearth the bad in evasive malware 

Most machine learning models are trained on a mix of malicious and clean features. Attackers routinely try to throw these models off balance by stuffing clean features into malware. Monotonic models are resistant against adversarial attacks because they are trained differently: they only look for malicious features. The magic is this: Attackers can’t evade a monotonic model by adding clean features. To evade a monotonic model, an attacker would have to remove malicious features.

Retain Microsoft Security Experts

Microsoft Security Experts are now available to strengthen your team with managed security services. Learn how to defend against threats with security experts.

Published
4 min read

Preparing your enterprise to eliminate passwords 

If you’re a CIO, a CISO, or any other exec at a company who is thinking about digital security, the user name/password paradigm is more than a hassle, it’s a true security challenge, which keeps many of us up at night. Today, I’m outlining the basic steps necessary to eliminate passwords, with the acknowledgement that we’re still on the journey. I believe we’ve mapped out the right path, but we aren’t finished yet.