Conference on Applied Machine Learning in Information Security (CAMLIS) 2023
The Conference on Applied Machine Learning in Information Security (CAMLIS) brings together scholars and practitioners to talk about applied and foundational machine learning research in information security.
They seek submissions of papers and/or extended abstracts on the direct application or adaptation of statistics, machine learning, deep learning, and data science to information security-related fields. Furthermore, accepted papers may be included in proceedings that are indexable by major academic search engines (e.g., Google Scholar).
They are seeking innovative contributions for consideration in the proceedings. Works that have recently been presented at other venues (since January 2021) are eligible to submit a non-archival talk/poster but will not be considered for the official proceedings.
The conference will be single-track, with presentations, posters, and tutorials. Presentations will last 20 minutes, with a substantial (up to 10-minute) discussion period following each one. This year, they also welcome tutorial suggestions on either machine-learning techniques or information security issues. Tutorials should be 60 minutes long and focus on mature areas of applied research or practice. Preference will be given to instructional subjects that have widespread applicability to and/or pique the CAMLIS community’s attention. All speeches and tutorials will be recorded and made available to the public following the conference.
They invite participation from information security academics, government research labs, national laboratories, and FFRDCs, as well as information security data scientists in the industry.
Conference on Applied Machine Learning in Information Security
The Conference on Applied Machine Learning in Information Security (CAMLIS) brings together scholars and practitioners to talk about applied and foundational machine learning research in information security.
They accept two sorts of submissions:
- A full-length paper for consideration as a presentation or poster
- An extended abstract submission for consideration as a poster, demo, or talk.
Submissions should concentrate on the direct application or modification of statistics, machine learning, deep learning, data analytics, and/or data science to information security-related fields.
Accepted talks will be presented as 20-minute sessions with up to 10 minutes of discussion time after each. The talks will also be videotaped and made public after the conference.
During the CAMLIS event, the poster session will be held live and in person.
They invite participation from information security academics, government research labs, national laboratories, and FFRDCs, as well as information security data scientists in the industry.
