1st Workshop of Security and Privacy in Artificial Intelligence

held in conjunction with AsiaCCS 2020

Taipei, Taiwan, June 1 2020

About SPAI

Security and Privacy in Artificial Intelligence (SPAI) is a single track workshop covering state-of-the-art research between the intersection of security & privacy and latest AI research. AI research provides novel solutions for traditionally challenging problems such as spam detection, DLP, and malware analysis. These solutions are radically changing the landscape of the security industry and how we approach new class of threats. At SPAI, we welcome research solving traditional security problems with AI technologies in a way that outperforms existing methods.

Additionally, as the usage of AI technologies in the security industry increases , we must consider the implication of this new technology. Given AI-based security solutions are fundamentally different than traditional rule-based solutions, there are additional attack vectors against these security solutions themselves. For example, developing adversarial samples to evade the current machine learning mechanism is a new class of security issue arisen from the usage of AI in security. SPAI provide a platform for researchers to present their latest work in this field.

Call for paper [cfp]

The interest to the workshop includes the following topic, but not limited to:

AI/ML Security

  • Adversarial attacks on machine learning and artificial intelligence
  • Defenses against adversarial attacks
  • Foundation of Artificial Intelligence Security
  • Privacy issues and privacy-preserving machine learning
  • Unconscious bias in ML models in security

AL/ML Applications for Computer Security and Privacy

  • Malware detection and analysis
  • Intrusion detection and classification
  • Data leak detection and Data loss prevention
  • Data anonymization and de-anonymization
  • Spam, phishing, and bot detection
  • Vulnerability discovery and automation
  • Threat intelligent management and monitoring
  • Novel industrial use cases for adapting AL/ML for security and privacy

Important Dates:

  • Submission due: January 31, 2020 (extended to February 7th 23:59PM PST)
  • Notification: March 4, 2020
  • Camera-ready due: March 15, 2020
  • Workshop: June 1, 2020

Submission Instruction:

Submission must be written in English, and layout in double-column ACM SIG Proceedings format, and should not exceed 8 page excluding biography and appendices (at most 10 pages in total). All submissions should be appropriately anonymized. Submitted papers must not substantially overlap papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Only PDF files will be accepted and authors of accepted papers must guarantee that their papers will be presented at the workshop. Position papers describing the work in progress are also welcome. At least one author of the paper must be registered at both the main AsiaCCS conference and this workshop. Accepted papers will be published in the ACM Digital Library.

Paper submission link: https://easychair.org/conferences/?conf=spai2020

Organizer:

Workshop Organizer:

  • Yueh-Hsun Lin, Apple
  • Xinyu Xing, Pennsylvania State University


Programming Committees:

  • Mohammad Al-Rubaie, Facebook
  • Pin-Yu Chen, IBM Research
  • Yueqiang Cheng, Baidu Research
  • Morten Dahl, Dropout Labs
  • Neil Gong, Duke University
  • Wenbo Guo, Pennsylvania State University
  • Peng Li, Baidu Research
  • Tongbo Luo, JD.COM R&D Center
  • Pengfei Sun, Shape Security
  • Fengguo Wei, Google
  • Johnny Wang, Google
  • Lun Wang, UC Berkeley
  • Ting Wang, Pennsylvania State University
  • Jankins Zhan, Netskope

Contact:

  • spai2020@easychair.org