[PET] CFP: DLS 2019 -- 2nd Deep Learning and Security Workshop (Due on December 14th, 2019)

Christian Wressnegger c.wressnegger at tu-bs.de
Thu Nov 29 07:08:52 GMT 2018

** Apologies if you receive multiple copies of this message **

Dear all,

we would like to inform you about this year's call for papers of the
DLS workshop 2019. This workshop strives for bringing two complementary
views together by (a) exploring deep learning as a tool for security as
well as (b) investigating the security of deep learning. The Please find
the CFP below.

Kind regards,
Christian Wressnegger.

2nd Deep Learning and Security Workshop

Thursday, May 23, 2019,
co-located with the 40th IEEE Symposium on Security and Privacy,

## Important Dates

* Paper Submission Deadline: December 14, 2018 (AoE, UTC-12)
* Acceptance Notice to Authors: February 15, 2019
* Publication-ready Papers Due: TBA
* Workshop date: Thursday, May 23, 2019

## Overview

Deep learning and security have made remarkable progress in the last
years.  Neural networks have been recognized as an essential tool for
security in academia and industry, for example, for detecting attacks,
analyzing malicious code or uncovering vulnerabilities in software.
At the same time, the security of deep learning has gained focus in
research and novel types of attacks against neural networks have been
explored, such as adversarial perturbations, neural backdoors, and
membership inference attacks.

This workshop strives for bringing these two complementary views
together by (a) exploring deep learning as a tool for security as well
as (b) investigating the security of deep learning.  The workshop is
aimed at academic and industrial researchers.

## Topics of Interest

DLS seeks contributions on all aspects of deep learning and security.
Topics of interest include (but are not limited to):

### Deep Learning
- Deep learning architectures for program embedding
- Deep learning methods for program similarity
- Deep program learning
- Modern deep NLP
- Recurrent network architectures
- Neural networks for graphs
- Neural Turing machines
- Semantic knowledge-bases
- Generative adversarial networks
- Relational modeling and prediction
- Deep reinforcement learning
- Attacks against deep learning
- Resilient and explainable deep learning

### Security Applications
- Computer forensics
- Spam detection
- Phishing detection and prevention
- Botnet detection
- Intrusion detection and response
- Malware identification, analysis and similarity
- Data anonymization/ de-anonymization
- Security in social networks
- Vulnerability discovery

## Paper Submissions

You are invited to submit papers of up to six pages, plus one page for
references.  To be considered, papers must be received by the
submission deadline (see Important Dates).  Submissions must be
original work and may not be under submission to another venue at the
time of review.

Papers must be formatted for US letter (not A4) size paper.  The text
must be formatted in a two-column layout, with columns no more than
9.5 in.  tall and 3.5 in.  wide.  The text must be in Times font,
10-point or larger, with 11-point or larger line spacing.  Authors are
strongly recommended to use the latest IEEE conference proceedings
templates.  Failure to adhere to the page limit and formatting
requirements are grounds for rejection without review.

For further details on the submission process, please visit the
workshop website: https://www.ieee-security.org/TC/SPW2019/DLS/

## Presentation Form

All accepted submissions will be presented at the workshop and
included in the IEEE workshop proceedings.  Due to time constraints,
accepted papers will be selected for presentation as either talk or
poster based on their review score and novelty.  Nonetheless, all
accepted papers should be considered as having equal importance,

One author of each accepted paper is required to attend the workshop
and present the paper for it to be included in the proceedings.

For any questions, contact the workshop organizers at:
dls2019 at sec.tu-bs.de

## Organization

### Workshop Chair
Nikolaos Vasiloglou, Relational AI & Georgia Institute of Technology

### Program Committee Chair
Konrad Rieck, TU Braunschweig

### Program Committee Co-Chair
Battista Biggio, University of Cagliari

### Steering Committee
Roberto Perdisci, University of Georgia & Georgia Institute of Technology
Ian Goodfellow, Google Brain
David Evans, University of Virginia

### Technical Program Committee
Hyrum Anderson, Endgame
Aylin Caliskan, George Washington University
Yinzhi Cao, John Hopkins University
Alvaro Cardenas, University of Texas at Dallas
Nicolas Carlini, Google Brain
Lorenzo Cavallaro, King's College London
Shang-Tse Chen, Georgia Institute of Technology
Yizheng Chen, Columbia University
Baris Coskun, Amazon Web Services
Brendan Dolan-Gavitt, New York University
Javier Echauz, Symantec Research
David Freeman, Facebook
Giorgio Giacinto, University of Cagliari
Neil Gong, Iowa State University
Guofei Gu, Texas A&M University
Xinyu Guo, Pennsylvania State University
Yufei Han, Symantec Research
Pavel Laskov, University of Liechtenstein
Kang Li, University of Georgia
Arsalan Mosenia, Princeton University
Erwin Quiring, TU Braunschweig
Tummalapalli Sudhamsh Reddy, Kayak Software
Kevin Roundy, Symantec Research Labs
Gianluca Stringhini, Boston University
Sai Deep Tetali, Google
Florian Tramer, Stanford University
Philip Tully, FireEye

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