1st Deep Learning and Security Workshop
Date: May 23, 2018 11:00 pm – May 24, 2018 11:00 am
Location: San Francisco, CA
"Over the past decade, machine learning methods have found their way into a large variety of computer security applications, including accurate spam detection, scalable discovery of new malware families, identifying malware download events in vast amounts of web traffic, detecting software exploits, blocking phishing web pages, and preventing fraudulent financial transactions, just to name a few. At the same time, machine learning methods themselves have evolved. In particular, Deep Learning methods have recently demonstrated great improvements over more “traditional” learning approaches on a number of important tasks, including image and audio classification, natural language processing, machine translation, etc. Moreover, areas such as program induction and neural abstract machines have made it possible to generate and analyze programs in depth. It is therefore natural to ask how the success of these deep learning methods may be translated to advancing the state-of-the-art in security applications.This workshop is aimed at academic and industrial researchers interested in the application of deep learning methods to computer security problems."
Submitted by grigby1 CPVI
on
"Over the past decade, machine learning methods have found their way into a large variety of computer security applications, including accurate spam detection, scalable discovery of new malware families, identifying malware download events in vast amounts of web traffic, detecting software exploits, blocking phishing web pages, and preventing fraudulent financial transactions, just to name a few. At the same time, machine learning methods themselves have evolved. In particular, Deep Learning methods have recently demonstrated great improvements over more “traditional” learning approaches on a number of important tasks, including image and audio classification, natural language processing, machine translation, etc. Moreover, areas such as program induction and neural abstract machines have made it possible to generate and analyze programs in depth. It is therefore natural to ask how the success of these deep learning methods may be translated to advancing the state-of-the-art in security applications.This workshop is aimed at academic and industrial researchers interested in the application of deep learning methods to computer security problems."