Conference on Applied Machine Learning for Information Security (CAMLIS)
October 12-13, 2018
The deluge of information security data invites data-driven strategies for information security situational awareness, threat detection and remediation. Statistics and machine learning approaches applied to assess and automate elements of information security have become increasingly popular in academia, government, national labs, and in industry, but with few venues for collegial information exchange in detail appropriate for data science practitioners in the information security space.
The Conference on Applied Machine Learning in Information Security (CAMLIS) is a venue for discussing applied research on machine learning, deep learning and data science in information security.
We invite title and abstract submissions on the direct application of statistics, machine learning, deep learning and data science to infosec relevant areas including:
– Insider threat detection
– Network and endpoint forensics
– Governance, compliance and exfiltration detection
– Detection of script-based and malware-less attacks
– Automated malware detection and classification
– Vulnerability assessment
– Machine learning models as attack surface
We encourage submissions that include analytic or predictive themes:
– Statistical analysis on large and small datasets
– Unique considerations of base-rate fallacy for data science in information security
– Infosec data sources and exploratory data analysis
– Unique approaches to dataset visualization
– Adversarial machine learning in the context of infosec
– Original or cross-domain deep learning architectures applied to information security data
– Natural language processing, image analysis, signal analysis
– Reinforcement learning for automating security tasks
– Unsupervised and semi-supervised approaches
– Explainable ML for Infosec
We invite both original submissions and presentations submitted very recently at other venues (since Jan 2018). We require only title and abstract (max 500 words) for submission, but speakers are also highly encouraged to publicly document their work after the conference in some form other than the presentation materials (for example a blog post, arxiv paper, github code, peerlyst, etc.).
Talks will be 20 minutes with a lengthy (up to 10 minutes) opportunity for discussion period after each talk. Talks will also be recorded and made publicly available after the conference.
We encourage participation from academics working in information security, government research labs, national laboratories and FFRDCs, and information security data scientists in industry.
Important dates are:
CFP is now open!
June 30: Abstract deadline
July 30: Speakers notified
October 12-13: Conference
Submit your abstract here: https://goo.gl/forms/pjGL3BmQyaLmM3tl1