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WoRMA 2023 : 2nd Workshop on Robust Malware Analysis


When Jul 7, 2023 - Jul 7, 2023
Where Delft, The Netherlands
Submission Deadline Mar 15, 2023
Notification Due Apr 30, 2023
Final Version Due May 15, 2023
Categories    malware analysis   security   machine learning   robust methods

Call For Papers


2nd WORKSHOP ON ROBUST MALWARE ANALYSIS (WORMA) co-located with EuroS&P 2023 on July 7, 2023 in Delft, The Netherlands.

## Important Dates

- Paper submission deadline: March 15, 2023; 11:59 PM (AoE, UTC-12)
- Acceptance notification: April 30, 2023; 11:59 PM (AoE, UTC-12)
- Camera ready due: May 15, 2023; 11:59 PM (AoE, UTC-12)
- Workshop date: July 7, 2023

## Overview

Malware research is a discipline of information security that aims to provide protection against unwanted and dangerous software. Since the mid-1980s, researchers in this area are leading a technological arms race against creators of malware. Many ideas have been proposed, to varying degrees of effectiveness, from more traditional systems security and program analysis to the use of AI and Machine Learning. Nevertheless, with increased technological complexity and despite more sophisticated defenses, malware’s impact has grown, rather than shrunk. It appears that the defenders are continually reacting to yesterday’s threats, only to be surprised by their today’s minor variations.

This lack of robustness is most apparent in signature matching, where malware is represented by a characteristic substring. The fundamental limitation of this approach is its reliance on falsifiable evidence. Mutating the characteristic substring, i.e., falsifying the evidence, is effective in evading detection, and cheaper than discovering the substring in the first place. Unsurprisingly, the same limitation applies to malware detectors based on machine learning, as long as they rely on falsifiable features for decision-making. Robust malware features are necessary.

Furthermore, robust methods for malware classification and analysis are needed across the board to overcome phenomena including, but not limited to, concept drift (malware evolution), polymorphism, new malware families, new anti-analysis techniques, and adversarial machine learning, while supporting robust explanations. This workshop solicits work that aims to advance robust malware analysis, with the goal of creating long-term solutions to the threats of today’s digital environment. Potential research directions are malware detection, benchmark datasets, environments for malware arms race simulation, and exploring limitations of existing work, among others.

## Topics of Interest

Topics of interest include (but are not limited to):

### Malware Analysis

Topics related to understanding the malicious actions exhibited by malware:
- Identification of malware behaviors
- Identification of code modules which implement specific behaviors
- Unsupervised behavior identification
- Machine Learning and AI for behavior identification
- Reliable parsing of file formats and program code
- De-obfuscation and de-cloaking of malware
- Robust static and dynamic code analysis
- Feature extraction in presence of adversaries
- Robust signature generation and matching

### Malware Detection

Topics related to techniques for malware detection:
- Developing robust malware detection, malware family recognition, identification of novel malware families
- Network-based malware analysis
- Host-based malware analysis
- Malware datasets: publication of new datasets for detection, e.g., family recognition, new family identification, behavior identification, generalization ability

### Malware Attribution

Topics exploring methods and techniques to confidently attribute a piece of malware to its creators:
- Binary and source-code attribution
- Adversarial attribution

### Malware Arms Race

Topics related to the malware arms race:
- Virtual malware arms race environments and competition reports – automated bots of malware and detectors simultaneously attacking and defending networked hosts, adaptively co-evolving in their quest towards supremacy
- Automated countermeasures to malware anti-analysis techniques, e.g., packing, anti-debugging, anti-emulation
- Bypassing anti-malware (anti-virus), e.g., via problem-space adversarial modifications

### Robustness Evaluations of Malware Analysis

Topics exploring the limitations of existing research:
- Experiments demonstrating the limitations in robustness of existing methods (for detection, unpacking, behavior analysis, etc.), datasets, defenses
- Machine learning-based malware analysis and adversarial machine learning
- Overcoming limitations – demonstrating methods resilient to, e.g., concept drift (malware evolution), polymorphism, new malware families, new anti-analysis techniques, or adversarial machine learning defenses

## Submission Guidelines

We invite the following types of papers:

- Original Research papers, which are expected to be 8 pages, not exceeding 12 pages in double-column IEEE format including the references and appendices. This category of papers should describe original work that is not previously published or concurrently submitted elsewhere.

- Position or open-problem papers, of up to 6 pages, using the same template (title for this category must include the text "Position:” at the beginning). Position research papers aim at fostering discussion and collaboration by presenting preliminary research activities, work in progress and/or industrial innovations. Position research papers may summarize research results published elsewhere or outline new emerging ideas.

- Reproducibility papers, of up to 8 pages (title for this category must include the text "Reproduction Report:” or “Reproducing…” at the beginning). This is a new, experimental category we are introducing to solicit re-implementation and open-source release of important papers in malware analysis and detection for which source code is not publicly available. The submission needs to include a 5-10 minute video tutorial with clear reproducibility steps. The paper needs to include insights into the main challenges and limitations. In addition to the submission, your prototype will also be evaluated: your prototype needs to have good documentation, with clear computational requirements and an easy interface to reproduce results from the original papers, or - if not - dive deeper into the reasons for why that was not possible.

Submissions must be anonymous (double-blind review), and authors should refer to their previous work in the third-person. Submissions must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or conference with proceedings.

Papers must be typeset in LaTeX in A4 format (not "US Letter") using the IEEE conference proceeding template supplied by EuroS&P ( at the following URL: Please do not use other IEEE templates.

Submissions must be in Portable Document Format (.pdf). Authors should pay special attention to unusual fonts, images, and figures that might create problems for reviewers. Your document should render correctly in Adobe Reader XI and when printed in black and white.

Accepted papers will be published in IEEE Xplore. One author of each accepted paper is required to attend the workshop and present the paper for it to be included in the proceedings. Committee members are not required to read the appendices, so the paper should be intelligible without them. Submissions must be in English and properly anonymized.

## Submission Site

Submissions will open soon...


## Workshop Program Chairs
- Fabio Pierazzi, King's College London, UK
- Nedim Šrndić, Huawei's Munich Research Center, Germany

## Steering Committee
- Lorenzo Cavallaro, University College London, UK
- Pavel Laskov, University of Liechtenstein, Liechtenstein
- Konrad Rieck, TU Braunschweig, Germany
- Daniele Sgandurra, Huawei's Munich Research Center, Germany

## Program Committee
To be announced...


The first edition of WoRMA took place in 2022, co-located with AsiaCCS in Nagasaki, Japan (

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