20 citations · 88 across the 21 of their papers we have counts for
4 papers · 1 filter
Adversarial robustness via stochastic regularization of neural activation sensitivity
Gil Fidel, Ron Bitton, Ziv Katzir +1
Recent works have shown that the input domain of any machine learning classifier is bound to contain adversarial examples. Thus we can no longer hope to immune classifiers against…
An Automated, End-to-End Framework for Modeling Attacks From Vulnerability Descriptions
Hodaya Binyamini, Ron Bitton, Masaki Inokuchi +3
Attack graphs are one of the main techniques used to automate the risk assessment process. In order to derive a relevant attack graph, up-to-date information on known attack techni…
Autosploit: A Fully Automated Framework for Evaluating the Exploitability of Security Vulnerabilities
Noam Moscovich, Ron Bitton, Yakov Mallah +5
The existence of a security vulnerability in a system does not necessarily mean that it can be exploited. In this research, we introduce Autosploit -- an automated framework for ev…
GIM: Gaussian Isolation Machines
Guy Amit, Ishai Rosenberg, Moshe Levy +3
In many cases, neural network classifiers are likely to be exposed to input data that is outside of their training distribution data. Samples from outside the distribution may be c…