5th Deep Learning and
Security Workshop
co-located with the 43rd IEEE Symposium on Security and Privacy
May 26, 2022
Photo: Pixabay


Title TBA
Alina Oprea, Northeastern University

Abstract: TBA
Bio: Alina Oprea is an Associate Professor at Northeastern University in the Khoury College of Computer Sciences. She joined Northeastern University in Fall 2016. Before that, she was a Consultant Research Scientist at RSA Laboratories, working on threat detection, machine learning for security, cloud security, and applied cryptography. Alina is the recipient of the Technology Review TR35 award for research in cloud security in 2011 and the recipient of the Google Security and Privacy Award 2019.

Title TBA
Brendan Dolan-Gavitt, NYU

Abstract: TBA
Bio: Brendan Dolan-Gavitt is an Assistant Professor in the Computer Science and Engineering Department at NYU Tandon. He holds a Ph.D. in computer science from Georgia Tech (2014) and a BA in Math and Computer Science from Wesleyan University (2006). Dolan-Gavitt's research interests span many areas of cybersecurity, including program analysis, virtualization security, memory forensics, and embedded and cyber-physical systems. His research focuses on developing techniques to ease or automate the understanding of large, real-world software systems in order to develop novel defenses against attacks, typically by subjecting them to static and dynamic analyses that reveal hidden and undocumented assumptions about their design and behavior. His work has been presented at top security conferences such as the ACM Conference on Computer and Communications Security (CCS) and the IEEE Symposium on Security and Privacy. He also led the development of PANDA, an open-source platform for architecture-neutral dynamic analysis, which has users around the world and has been featured in technical press such as The Register. His most recent work, which focuses on developing techniques to probe industrial control systems for vulnerabilities, has been funded by the Office of Naval Research. Prior to joining NYU, he was a postdoctoral researcher at Columbia University.

Call for Papers

Important Dates

  • Paper submission deadline: Feb 1, 2022, 11:59 PM (AoE, UTC-12)
  • Acceptance notification: Mar 1, 2022
  • Camera-ready due: Mar 17, 2022
  • Workshop: May 26, 2022


Deep learning and security have made remarkable progress in the last years. On the one hand, neural networks have been recognized as a promising tool for security in academia and industry. On the other hand, the security of deep learning has gained focus in research, the robustness of neural networks has recently been called into question.

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.

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 for program embedding and 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

Computer Security

  • 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

Submission Guidelines

You are invited to submit original research papers of up to six pages, plus additional 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. Submissions must be in English and properly anonymized.

For any questions, contact the workshop organizers at dls2022@ieee-security.org

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.

Submission Site



Workshop Chair

Program Chair

Program Co-Chair

Steering Committee

Program Committee

  • Ambra Demontis, University of Cagliari
  • Andrew Ilyas, Massachusetts Institute of Technology
  • Battista Biggio, University of Cagliari
  • Brendan Dolan-Gavitt, New York University
  • Chao Zhang, Tsinghua University
  • Christian Wressnegger, Karlsruhe Institute of Technology (KIT)
  • Daniel Arp, TU Berlin
  • Davide Maiorca, University of Cagliari
  • Erwin Quiring, TU Braunschweig
  • Evan Downing, Georgia Institute of Technology
  • Feargus Pendlebury, Facebook
  • Giorgio Giacinto, University of Cagliari
  • Giovanni Apruzzese, University of Liechtenstein
  • Heng Yin, University of California, Riverside
  • Ivan Evtimov, Meta AI
  • Kevin Roundy, NortonLifeLock
  • Kexin Pei, Columbia University
  • Konrad Rieck, TU Braunschweig
  • Liang Tong, NEC Labs
  • Matthew Jagielski, Google
  • Min Du, Palo Alto Networks
  • Mohammadreza (Reza) Ebrahimi, University of South Florida
  • Mu Zhang, University of Utah
  • Nicholas Carlini, Google
  • Philip Tully, ZeroFOX
  • Reza Shokri, National University of Singapore
  • Sagar Samtani, Indiana University
  • Sanghyun Hong, Oregon State University
  • Scott Coull, Mandiant
  • Shruti Tople, Microsoft Research
  • Teodora Baluta, National University of Singapore
  • Tianhao Wang, University of Virginia
  • Tummalapalli S Reddy, University of Texas at Arlington
  • Varun Chandrasekaran, University of Wisconsin-Madison
  • Weilin Xu, Intel Labs
  • Yacin Nadji, Corelight Inc
  • Yang Zhang, CISPA Helmholtz Center for Information Security
  • Yinzhi Cao, Johns Hopkins University
  • Ziqi Yang, Zhejiang University