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CYSARM '21: Proceedings of the 3rd Workshop on Cyber-Security Arms Race
ACM2021 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security Virtual Event Republic of Korea 19 November 2021
ISBN:
978-1-4503-8661-6
Published:
15 November 2021
Sponsors:
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October 13 - 17, 2025
Taipei , Taiwan
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Abstract

It is our great pleasure to welcome you to the 3rd Workshop on Cyber-Security Arms Race (CYSARM)! This year we are thrilled to continue chairing this workshop at a prestigious venue as the ACM Conference on Computer and Communications Security (CCS). Although CYSARM is at the early phases (this year marks the third edition of this workshop), the workshop is already fostering collaboration among researchers and practitioners to discuss the various facets and trade-offs of cyber-security. Being the first workshop of its kind, CYSARM benefits the cyber-security community by addressing novel (and often controversial) topics in cyber-security, such as trade-offs and double-edged sword techniques. Beyond the study of cyber-security, privacy and trust as standalone components, it is also important to look at how to balance their trade-offs especially when it comes to several contradicting requirements, such as security vs privacy, security vs trust, and security vs usability. CYSARM considers all complex facets and double-edged sword aspects of the cyber-security ecosystem, in particular, how new technologies and algorithms might impact the cyber-security of existing or future models and systems.

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SESSION: Paper Session 1
research-article
The More, the Better: A Study on Collaborative Machine Learning for DGA Detection

Domain generation algorithms (DGAs) prevent the connection between a botnet and its master from being blocked by generating a large number of domain names. Promising single-data-source approaches have been proposed for separating benign from DGA-...

research-article
Multi-Stage Attack Detection via Kill Chain State Machines

Today, human security analysts need to sift through large volumes of alerts they have to triage during investigations. This alert fatigue results in failure to detect complex attacks, such as advanced persistent threats (APTs), because they manifest ...

SESSION: Paper Session 2
research-article
Open Access
Your Smart Contracts Are Not Secure: Investigating Arbitrageurs and Oracle Manipulators in Ethereum

Smart contracts on Ethereum enable billions of dollars to be transacted in a decentralized, transparent and trustless environment. However, adversaries lie await in the Dark Forest, waiting to exploit any and all smart contract vulnerabilities in order ...

short-paper
Regulation TL;DR: Adversarial Text Summarization of Federal Register Articles

Short on time with a reduced attention span, people disengage from reading long text with a "too long, didn't read" justification. While a useful heuristic of managing reading resources, we believe that "tl;dr" is prone to adversarial manipulation. In a ...

Contributors
  • Royal Holloway, University of London
  • Ubitech Ltd.
  • Huawei Technologies Deutschland GmbH
  1. Proceedings of the 3rd Workshop on Cyber-Security Arms Race

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