Co-hosted with Align; registration required

Speakers: Dr. Rachel Allen and Becca Lynch

Speaker: Hyrum Anderson

Speaker: Nathaniel Fick, CEO/Investor/U.S. Ambassador/Marine/Author

After building the cybersecurity software company Endgame, Nate Fick served from 2022-2025 as the inaugural U.S. Ambassador for Cyberspace & Digital Policy at the Department of State, leading American diplomacy around the world on technology issues including cybersecurity, digital infrastructure, digital regulatory policy, and emerging technologies. From Kyiv to Beijing, and from Brussels to Delhi, he was on the frontlines of the competition to shape the 21st century -- a competition increasingly decided by key technologies. His keynote shares lessons relevant to citizens, investors, and company-builders alike.

About: This session focuses on diverse methods for identifying, analyzing, and understanding various types of cyber threats and vulnerabilities, ranging from malware and code flaws to social and financial fraud.

MADAR: Efficient Continual Learning for Malware Analysis with Diversity-Aware Replay

Speaker: Mohammad Saidur Rahman

This study proposes MADAR, a Continual Learning (CL) framework for malware classification, which addresses catastrophic forgetting by incorporating diversity-aware replay. It demonstrates improved detection accuracy for both Windows and Android malware datasets.

Reason. Search. Retrieve. Repeat. Iterative Retrieval for Automating Vulnerable Code Discovery

Speaker: Supriti Vijay

This paper presents a multi-turn retrieval architecture for automating vulnerable code discovery, where models iteratively generate and refine search queries. It introduces a reinforcement learning environment and dataset for training such strategies.

Social Attack Surfaces: Emerging Cybersecurity Threats in Open Source Collaboration

Speaker: Christopher Honaker

This research examines social interactions in open-source code repositories using a biased BERTopic model to identify emerging cybersecurity threats (e.g., the XZ Utils backdoor) by prioritizing negative sentiment and cybersecurity keywords.

Adversarial Machine Learning Attacks on Financial Reporting via Maximum Violated Multi-Objective Attack

Speaker: Edward Raff

This work explores Adversarial Machine Learning (AML) attacks on financial reporting, demonstrating how bad actors can manipulate financial statements to inflate earnings and reduce fraud scores simultaneously, highlighting a critical information security vulnerability in financial systems.

About: This concluding session addresses practical, real-world applications of machine learning in Security Operations Centers (SOCs), focusing on detection frameworks, authentication security, and advanced threat intelligence.

Democratizing ML for Enterprise Security: A Self-Sustained Attack Detection Framework

Speaker: Sadegh Momeni

This paper proposes a two-stage hybrid framework for ML-based threat detection in enterprise security, combining loose YARA rules with an ML classifier and leveraging synthetic data generation (Simula) and active learning to achieve a self-sustained, low-overhead solution for SOCs.

Evaluating Risk-Based Authentication Effectiveness in Production 2FA Systems

Speaker: Steven Leung

This study provides the first large-scale empirical evaluation of Risk-Based Authentication (RBA) effectiveness in production two-factor authentication (2FA) systems against real-world opportunistic, targeted, and advanced attacks. It demonstrates how heuristic and anomaly detection methods improve security while maintaining user experience.

LLM ATT&CK Navigator: Mapping Observed Generative Adversarial Techniques Across the Cyber Killchain

Speaker: Kyla Guru

This work introduces the LLM ATT&CK Navigator, an interactive tool that maps real-world instances of AI-enabled misuse onto the MITRE ATT&CK Killchain and calculates enablement risks. This provides actionable insights into current adversarial tactics for defensive prioritization.

Speakers: Becca Lynch and Hyrum Anderson

CAMLIS Posters

1. A Platform for Rapidly Developing and Deploying Protection Against Large Language Models Attacks

   Presenter: Konstantin Berlin

2. Accelerating Cyber Defense with Applied Open-Weight LLMs

   Presenter: Ryan Fetterman

3. Anomaly Detection Betrayed Us, so We Gave It a New Job: Enhancing Command-Line Classification with Benign Anomalous Data

   Presenter: Ben Gelman

4. Base Rate Measurement and Precision Forecasting

   Presenter: Michael Slawinski

5. Benchmarking Agentic LLMs for Vulnerability Management: Exposing and Mitigating Situational Awareness Bias

   Presenter: Dmitrijs Trizna

6. Causal Reinforcement Learning for Labelling Optimization in Cyber Anomaly Detection

   Presenter: Susan Babirye

7. Dynamic Graph Structure for Tracking Cluster Evolution and LLM Summarization

   Presenter: Michael Slawinksi

8. Evaluating LLM Generated Detection Rules in Cybersecurity

   Presenter: Anna Bertiger

9. Glass-box triage: An explainable-by-design LLM-ML-Human framework for high scale production threat detection

   Presenter: Caleb Fogleman

10. Harnessing Large Language Models for Detection of AI Generated Attacks

    Presenter: Abhishek Singh

11. Mutually-exciting point processes and topic modelling of honeypot computer terminal data

    Presenter: Daniyar Ghani

12. Offensive Security for AI Systems: Concepts, Practices, and Applications

    Presenter: Josh Harguess

13. PentestJudge: Autonomous Process Evaluation for AI Security Agents

    Presenter: Shane Caldwell

14. RADAR: Open-Source Detection of Agentic Deception and Alignment Risk in LLMs

    Presenter: Edward Joseph

15. RoleSentry: A Multi-Stage Framework for Explainable Detection of AWS Role Chaining Attacks

    Presenter: Godwin Attigah

CAMLIS Red Posters

1. Ask What Your Country Can Do For You: Towards a Public Red Teaming Model

   Presenter: Wm. Matthew Kennedy

2. Detecting Complex Vulnerabilities in Real-World Code - New Benchmark for Enhanced Software Security

   Presenter: Klaudia Kloc

3. LLM backdoor poisoning: attacks and detections

   Presenter: Nir Rosen