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AISEC 2019 : 12th ACM Workshop on Artificial Intelligence and Security

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Conference Series : Security and Artificial Intelligence
 
Link: https://aisec.cc/
 
When Nov 15, 2019 - Nov 15, 2019
Where London, UK
Submission Deadline Jun 21, 2019
Notification Due Aug 7, 2019
Final Version Due Aug 20, 2019
Categories    cyber security   artificial intelligence   machine learning   privacy
 

Call For Papers

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CALL FOR PAPERS

ACM Workshop on Artificial Intelligence and Security (AISec) 2019
co-located with the 26th ACM Conference on Computer and Communications Security

November 15, 2019, London, UK

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Workshop Website:
https://aisec.cc/


Call
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Recent years have seen a dramatic increase in applications of artificial intelligence, machine learning, and data mining to security and privacy problems.
The use of AI and ML in security-sensitive domains, in which adversaries may attempt to mislead or evade intelligent machines, creates new frontiers for security research.
The recent widespread adoption of deep learning techniques, whose security properties are difficult to reason about directly, has only added to the importance of this research.
The AISec workshop, now in its 12th year, is the leading venue for presenting and discussing new developments in the intersection of security and privacy with AI and machine learning.


Important information
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Submission link: https://aisec2019.hotcrp.com/
Paper submission deadline: June 21, 2019, 11:59 PM (AoE, UTC-12)
Reviews released: August 1, 2019
Author response due: August 4, 2019
Acceptance notification: August 7, 2019
Camera ready due: August 30, 2019 (hard deadline)
Workshop: November 15, 2019


Topics of interest
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Topics of interest include, but are not limited to:

AI/ML Security

- Adversarial attacks on machine learning
- Defenses against adversarial attacks
- Security of deep learning systems
- Theoretical foundations of machine learning security
- Formal verification of machine learning models
- Differential privacy and privacy-preserving learning
- Explainability and Fairness

AI/ML for Computer Security

- Spam and phishing detection
- Botnet and malware detection
- Intrusion detection and response
- Computer forensics
- Data anonymization/de-anonymization
- Security in social networks
- Vulnerability discovery


Submissions
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We invite the following types of papers:

- Original research papers on any topic in the intersection of AI or machine learning with security, privacy, or related areas.

- Position and open-problem papers discussing the relationship of AI or machine learning to security or privacy. Submitted papers of this type may not substantially overlap with papers that have been published previously or that are simultaneously submitted to a journal or conference/workshop proceedings.

- Systematization-of-knowledge papers, which should distill the AI or machine learning contributions of a previously-published series of security papers.

Paper submissions must be at most 10 pages in double-column ACM format, excluding the bibliography and well-marked appendices, and at most 12 pages overall.
Papers should be in LaTeX in the new ACM format.
This format is required for the camera-ready version. Please follow the main CCS formatting instructions (except with page limits as described above).
In particular, we recommend using the CCS template, which can be downloaded from https://github.com/acmccs/format.
Accepted papers will be published by the ACM Digital Library and/or ACM Press. 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 link: https://aisec2019.hotcrp.com

For questions about the submission process, please contact the
workshop co-chairs.


Committee
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Workshop Chairs
- Sadia Afroz, ICSI, UC Berkeley, USA
- Battista Biggio, University of Cagliari & PluribusOne, Italy
- Nicolas Carlini, Google Brain, USA
- Yuval Elovici, Ben-Gurion University of the Negev, Israel
- Asaf Shabtai, Ben-Gurion University of the Negev, Israel

Steering Committee
- David Freeman, Facebook, Inc.
- Benjamin Rubinstein, University of Melbourne

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