1.1k citations · 1.9k across the 11 of their papers we have counts for
13 papers
Hopper: Modeling and Detecting Lateral Movement (Extended Report)
Grant Ho, Mayank Dhiman, Devdatta Akhawe +4
In successful enterprise attacks, adversaries often need to gain access to additional machines beyond their initial point of compromise, a set of internal movements known as latera…
A Large-Scale Analysis of Attacker Activity in Compromised Enterprise Accounts
Neil Shah, Grant Ho, Marco Schweighauser +3
We present a large-scale characterization of attacker activity across 111 real-world enterprise organizations. We develop a novel forensic technique for distinguishing between atta…
Detecting and Characterizing Lateral Phishing at Scale
Grant Ho, Asaf Cidon, Lior Gavish +5
We present the first large-scale characterization of lateral phishing attacks, based on a dataset of 113 million employee-sent emails from 92 enterprise organizations. In a lateral…
Stateful Detection of Black-Box Adversarial Attacks
Steven Chen, Nicholas Carlini, David Wagner
The problem of adversarial examples, evasion attacks on machine learning classifiers, has proven extremely difficult to solve. This is true even when, as is the case in many practi…
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye, Nicholas Carlini, David Wagner
We identify obfuscated gradients, a kind of gradient masking, as a phenomenon that leads to a false sense of security in defenses against adversarial examples. While defenses that…
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Nicholas Carlini, David Wagner
We construct targeted audio adversarial examples on automatic speech recognition. Given any audio waveform, we can produce another that is over 99.9% similar, but transcribes as an…