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abstract

AISec '23: 16th ACM Workshop on Artificial Intelligence and Security

Published: 21 November 2023 Publication History

Abstract

The use of Artificial Intelligence (AI) and Machine Learning (ML) has been the center of the most outstanding advancements in the last years. The ability to analyze considerable streams of data in real time makes these technologies the most promising tool in many domains, including cybersecurity. As an outstanding example, ML can be used for identifying malware because of its ability to detect patterns otherwise difficult to see for humans and hard-coded rules. As malware continues to evolve, ML will become increasingly important for keeping up with the latest threats. However, the use of AI and ML in security-relevant domains raised rightful concerns about their trustworthiness and robustness, especially in front of adaptive attackers. Additionally, privacy threats are now emerging as a crucial aspect and need proper testing and possibly mitigation to prevent data stealing and leakage of sensitive information. The AISec workshop provides a venue for presenting and discussing new developments in the intersection of security and privacy with AI and ML. The complete AISec'23 workshop proceedings are available at: https://dl.acm.org/doi/proceedings/10.1145/3576915.3624029.

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cover image ACM Conferences
CCS '23: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
November 2023
3722 pages
ISBN:9798400700507
DOI:10.1145/3576915
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 November 2023

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Author Tags

  1. adversarial machine learning
  2. artificial intelligence
  3. privacy
  4. security

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CCS '23
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Overall Acceptance Rate 1,261 of 6,999 submissions, 18%

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CCS '24
ACM SIGSAC Conference on Computer and Communications Security
October 14 - 18, 2024
Salt Lake City , UT , USA

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