Call For Papers

Conference Website: https://www.camlis.org/

Venue: Sands Capital Management, 1000 Wilson Boulevard, 30th Floor, Arlington, VA 22209

*Submit via Microsoft CMT: https://cmt3.research.microsoft.com/CAMLIS2026/Submission/Index

*Please note that all presentations are required to be in-person.

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

Important Dates

CFP Opens: Tuesday, April 7

CFP Closes: Friday, June 26

Accepted/Rejected Notifications: Friday, July 31

Submission info

The 2026 Conference on Applied Machine Learning in Information Security (CAMLIS) will be hosted at the offices of Sands Capital Management in Arlington, VA.  CAMLIS is a premier venue for researchers and practitioners from academia, industry, government, and FFRDCs to discuss the intersection of machine learning and cybersecurity. Our goal is to bridge the gap between theoretical ML research and operational security practice. We seek original work that applies AI, machine learning, deep learning, statistics, and data science to solve real-world information security challenges.

We invite authors to submit full length papers or extended abstracts for consideration for talks or poster session presentations. Full length papers will be eligible for our proceedings, hosted through the Proceedings of Machine Learning Research (PMLR).

Scope and Content

This year, talks may take the form of a conventional research presentation or more hands-on workshops, e.g., demoing a novel research tool/approach. Regardless of the format of presentation, content must provide novel applied machine learning for infosec research innovations. CAMLIS is a research conference, not a trade show, so submissions that are simply showcasing vendor software will be rejected.

Topics of Interest

Submissions should focus on the direct application or adaptation of statistics, machine learning, deep learning, data analytics, and/or data science to infosec relevant areas including (but not limited to): 

Security for AI

  • Adversarial ML & Robustness

  • AI Risk & Governance

  • Generative AI & LLM Security

  • Privacy-Preserving ML


Threat Detection & Analysis

  • Advanced Malware Research

  • Phishing & Social Engineering

  • Binary & Advanced Malware Analysis

  • Cyber Threat Intelligence & Dark Web

Infrastructure & Network Security

  • Network & Endpoint Forensics

  • Cloud & Zero-Trust Architecture

  • Vulnerability Management

Security Operations (SecOps)

  • AI-Augmented SOC Applications

  • Insider Threat Detection

Governance, Risk, and Compliance (GRC)

  • Cybersecurity Risk Management: Overarching strategy for organizational risk.

  • Governance, Compliance & Data Exfiltration: Merges regulatory alignment with data protection oversight.

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 and ML Red Teaming 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

  • Multi-agent solutions

  • Unsupervised and semi-supervised approaches

  • Explainable ML for Infosec

  • Multi-view, multi-task, and multi-source learning

  • Uncertainty Estimation and Risk Measurement

  • Knowledge distillation and transfer learning paradigms

  • Graph embedding (node, edge, graph-level)

  • Large Language Models (LLMs) applications for InfoSec + Security vulnerabilities of LLMs

  • Security vulnerabilities of LLMs

  • AI Agents for InfoSec

Submission instructions

Papers/Abstracts will be submitted through Microsoft CMT: https://cmt3.research.microsoft.com/CAMLIS2026/Submission/Index.


We invite both original submissions and presentations submitted very recently at other venues (since January 2026) for conference talks and posters.

To be eligible for conference proceedings, submitted papers must contain sufficiently novel material (i.e., not a direct copy from other conference submissions) to avoid conflicts of interest and dual submission constraints.

Submissions must adhere to the following:

  • Double-Blind Review Policy: This means that no information identifying authors or a research group may be included in the paper. Prior work may be referenced but must be referenced in the 3rd person (e.g., “In [1] we did cool stuff” is not ok, but “in [1], Smith et al. did cool stuff” is ok).

  • Submission format: Submissions this year must be formatted according to a PMLR template: https://proceedings.mlr.press/spec.html 

  • Page Limits

    • Extended Abstract: 

      • Max 4 pages, not including references, PMLR template

    • Full Length Paper (Proceedings Eligible):

      • Min 10 pages PMLR template; Max 20 pages, not including references

  • AI Submission policy

    • AI may be used to proofread, enhance readability, and improve writing. Submissions that are purely AI generated will be desk-rejected.

Accepted Submissions

Accepted talks will be presented as talks of 20 minutes in length with up to 5 minutes of discussion period after each talk. Talks will also be recorded and made publicly available after the conference. The poster session will be held live and in person during the CAMLIS event. 

While not required, once accepted (i.e., after the double-blind review process), authors are encouraged to provide code, data, and documentation from their research in a publically accessible format or repository (e.g., GitHub). This will help to facilitate scientific reproducibility of impactful research within our community and help to generate innovative research in a timelier and streamlined manner.


We welcome talks with a hands-on or interactive component. If speakers wish for their session to be interactive, it should be noted in the abstract. CAMLIS will provide stable WiFi, but all other infrastructure (e.g. interactive notebooks) for the session is the responsibility of the speaker and we encourage speakers with interactive talks to plan for redundancy. 

Accepted posters will be provided with an easel and 36" x 48" board to fix your poster to. Portrait/tall orientation is recommended, no tri-folds.

2025 Proceedings

For examples of types submissions which get into CAMLIS, please refer to last year’s proceedings: https://proceedings.mlr.press/v299/ 

Questions

View our FAQ page. Please direct questions about CFP and/or submissions to Program@camlis.org. Please direct other questions (e.g., registration) to info@camlis.org.