IWSPA 2024 : The 10th ACM International Workshop on Security and Privacy Analytics

The 10th ACM International Workshop on Security and Privacy Analytics (IWSPA 2024), Co-located with The 14th ACM Conference on Data and Application Security and Privacy (ACM CODASPY 2024), will be held on June 21, 2024 in Porto, Portugal.

This is the tenth workshop in the series of workshops on Security and Privacy Analytics. Increasingly, sophisticated techniques from machine learning, data mining, statistics and natural language processing are being applied to challenges in security and privacy fields. However, experts from these areas have had few venues in the past where they can meet and exchange ideas so that strong collaborations can emerge, and cross-fertilization of these areas can occur. Moreover, current courses and curricula in security do not sufficiently emphasize background in these areas and students in security and privacy are not emerging with deep knowledge of these topics. Hence, we propose to continue the workshop that we started in 2015 to address the research and development efforts in which analytical techniques from machine learning, data mining, natural language processing and statistics are applied to solve security and privacy challenges (“security and privacy analytics”). Over the course of these seven years, the papers published in IWSPA proceedings have been downloaded more than 32,000 times according to ACM Digital Library and have 1000+ citations on Google Scholar.

Submissions of papers related to methodology, design, techniques and new directions for security and privacy that make significant use of machine learning, data mining, statistics or natural language processing are welcome. Furthermore, submissions on educational topics and systems in the field of security analytics are also highly encouraged. Proposals for tutorials on related topics are also welcome.

The workshop will focus on, but is not limited to, the following areas:
• Natural Language Processing for Security/Privacy
• Data Mining Techniques for Security/Privacy
• Machine Learning for Security/Privacy
• Statistics for Security/Privacy
• Inference Control
• Privacy-Preserving Data Mining
• Security of Machine Learning and Data Mining
• Security and Privacy of AI Systems and Large Language Models
• Security of Natural Language Processing
• Social Network Analysis
• Digital and Multimedia Forensics
• Applications of Blockchain for Security/Privacy
• Case Studies and/or datasets to support security/privacy research
• Educational Topics and Courses

The workshop is planned for one day, June 21, 2024. All submissions must describe original research, not published nor currently under review for another workshop, conference, or journal. All papers must be submitted electronically via EasyChair:
https://easychair.org/conferences/submission_new?a=31842285

Full papers for review must be at most 10 pages (12 pages in total) in length in double-column ACM format excluding bibliography and appendices, and short papers for review must be at most 6 pages (8 pages in total) in length in the same format as full papers.

Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM Digital Library. The presenter must register for the workshop before the deadline for author registration. The accepted papers will be compiled in the workshop proceedings as either a regular paper within 11 pages or a short paper within 7 pages. A limited number of high-quality submissions may be selected for publication in a special issue of a journal.

Important Dates:

Paper Submission Deadline: February 26, 2024 (Anywhere on Earth)
(Authors’ names and affiliations are not required to be withheld on submissions.)

Acceptance Notification: March 25, 2024

Camera Ready Submission Deadline: April 1, 2024

Workshop website: https://sites.google.com/view/iwspa-2024

Submission link: https://easychair.org/conferences/submission_new?a=31842285

For questions, contact any of the program co-chairs:

Hongxin Hu ([email protected])
Andrew H. Sung ([email protected])
Rakesh M. Verma ([email protected])