// THE SPEAKERS

There is no issue more important and yet less understood today than Cybersecurity. Our entire way of life, from communication to commerce to conflict, fundamentally depends on the Internet. The author of a book described by the chairman of Google as "an essential read" and by the head of NATO as "the most approachable and readable book ever written on the cyber world," Singer takes the audience through the key issues and questions that we all need to better understand.

TBD

Join us on a brief update on how the UC Cyber Security Programs continue to strengthen our proven foundations, to engineering the future of defense. The University of Charleston is setting the standard in cybersecurity education. We aren’t just teaching tech, we are forged to train the next generation of cybersecurity warriors. By blending elite technical skills with decisive leadership, UC is arming students to neutralize imminent threats and dominate in a fast-paced digital battlefield.

Cybersecurity risk isn’t a side dish—it belongs at the head table of enterprise risk management. In this session, Ian Frist, Director of Governance, Risk & Compliance at Corning, explores how organizations can stop treating cyber risk as a siloed technical concern and start integrating it into their broader risk appetite framework. Using real-world stories from the trenches (without naming names), Ian will unpack the consequences of misaligned appetites—where security teams over-restrict or under-protect due to unclear enterprise priorities. He’ll challenge the common misconception that cybersecurity risk appetite is just about controls and compliance, and show how it’s really about leadership, business context, and strategic clarity. Attendees will leave with: • A practical framework for aligning cyber risk appetite with enterprise risk appetite • Tips for communicating risk appetite across technical and non-technical stakeholders • A fresh perspective on how to “serve” cybersecurity risk in a way that satisfies the whole organization Whether you’re a seasoned GRC leader or just pulling up a chair to the risk table, this session will help you bring your appetite—and leave with a full plate of actionable insights.

Most cybersecurity guidance assumes you have a team. A SOC. A vendor. Someone else handling it. But a growing population of engineers, researchers, and practitioners are operating production-grade infrastructure entirely on their own — running dozens of containerized services, a fleet of IoT devices, and increasingly, local AI agents capable of acting autonomously on that infrastructure. What does serious security look like when the buck stops with you? This talk presents a practitioner’s end-to-end architecture for defense in depth across three interconnected layers: the homelab foundation, the smart home edge, and the AI intelligence layer — drawing from real-world implementation rather than theory. In the first act, we examine network segmentation philosophy for self-hosted stacks running Proxmox, Docker, and zero-trust overlay networks. We cover the most dangerous assumption homelabbers make — the flat network — fine-grained access control group design, secrets management, and why “Cloudflare tunnel plus Nginx Proxy Manager” is a deployment strategy, not a security posture. The second act turns to the IoT edge: the most chaotic, least-auditable layer of any home network. We examine what Zigbee, Z-Wave, and ESPHome actually provide in terms of authentication and encryption — and what they do not — the OTA firmware trust problem, and how a single compromised sensor can become a persistent foothold. A real smart infrastructure deployment covering power monitoring, environmental sensing, radar presence detection, and audio is used as a concrete attack surface case study. The final act addresses the emerging challenge that makes all of this more urgent: adding local AI agents that can act on your infrastructure. We explore why cloud AI is a non-starter for a privacy-first stack, how to architect a local-inference multi-agent system using open-weight models and scoped tool access, and the new threat vectors this introduces — prompt injection, MCP tool misuse, and agent privilege escalation. We close with a framework for treating AI as infrastructure, with all the security discipline that implies. Attendees will leave with a threat model, an architectural philosophy, and concrete implementation patterns applicable to any environment where a single operator is responsible for the full stack.

Large Language Models (LLMs) are used by millions of users worldwide to perform various tasks and have become a valuable tool for both individuals and businesses. Consistency and cybersecurity are two of the major concerns for LLMs' evaluation in order to increase the trustworthiness of their behavior. This study focuses on testing the security and consistency measures of the three most popular AI chatbots (i.e., ChatGPT-5, Google Gemini 2.5 Flash, Microsoft Copilot). We hypothesized that the output persistence would be high and the same within the models and across models, and all models would not leak the information that users input to other users through prompts. Twenty fabricated business plans, of which half were defined as "confidential" strings, were developed and input into the three LLMs. Extraction of the information was attempted every twenty-four hours for two consecutive weeks. Results were analyzed using the Jaccard similarity index to compare the outputs between LLMs, identify differences over time, analyze response patterns, and identify any risks in the leaking of information. Over time, all models demonstrated a low level of output consistency, indicating a poor behavior dependability assessment. The outputs of the three models were similar in content, but the expressions were different amongst them. Regarding security, it is unlikely that there was a leakage of confidential information.

What happens when a cyberattack takes down the power grid and you’re the team responsible for responding? This interactive virtual workshop places students in the middle of a simulated cyber incident targeting a U.S. power grid. Participants will step into roles across security, operations, and leadership as the scenario unfolds in real time, making decisions under pressure as new information (“injects”) is introduced. Through this guided tabletop exercise, students will explore how cyberattacks impact critical infrastructure, how defenders coordinate response efforts, and what trade-offs must be made when systems that people depend on cannot simply be shut down. The session introduces core concepts in incident response, risk, and resilience while also highlighting the real-world consequences of cyber failures in essential services. No prior experience is required! Just a willingness to think critically, collaborate, and step into the role of a cyber defender.

Cybersecurity education often focuses on traditional network threats, but students are increasingly entering a world shaped by blockchain systems, AI tools, digital assets, and decentralized infrastructure. This talk introduces the Blockchain Attack Lab, a hands-on educational model that uses real-world-inspired incident scenarios to teach cybersecurity fundamentals, attacker mindset, governance failures, and response strategy. The session will explain how blockchain and digital asset incidents can be used to help students understand threat modeling, incident response, smart contract risk, operational security, and decision-making under pressure. Rather than focusing on speculation or cryptocurrency prices, the talk frames blockchain as a practical cybersecurity training environment where technical, legal, business, and governance issues collide. Attendees will leave with a better understanding of how emerging technology scenarios can be used to prepare students for modern cyber threats and workforce opportunities.

As enterprise AI evolves from standalone large language models to autonomous multi-agent systems, cybersecurity faces a fundamental shift in how trust is established, monitored, and enforced. These intelligent agent ecosystems are capable of reasoning, collaborating, invoking enterprise tools, and making autonomous decisions across critical business processes. While this transformation promises significant gains in productivity and operational efficiency, it also introduces new attack surfaces that extend far beyond traditional application security. This presentation introduces a practical cybersecurity framework for securing enterprise multi-agent systems using Zero Trust principles. Rather than treating AI as a single protected application, the session demonstrates how every autonomous agent, orchestration service, memory store, vector database, external tool, and inter-agent communication channel must be considered an independent security principal requiring continuous authentication, authorization, validation, and monitoring. Drawing on the KnowledgeView reference architecture, attendees will explore how dedicated security, governance, and trust agents can continuously evaluate agent behavior, verify data provenance, detect prompt injection and retrieval poisoning, enforce least-privilege access, monitor autonomous decision making, and maintain immutable audit trails. The presentation also examines emerging threats including agent impersonation, memory poisoning, cross-agent trust exploitation, malicious tool invocation, and autonomous privilege escalation, along with architectural patterns that improve resilience, reliability, and operational trust. Attendees will leave with a reference architecture and implementation roadmap for designing secure, observable, and trustworthy enterprise AI ecosystems. As organizations move toward increasingly autonomous digital workforces, adopting Zero Trust for AI Agents provides a practical foundation for protecting enterprise systems while enabling responsible AI innovation.

Most enterprise networks assume their infrastructure is secure because they buy expensive vendor contracts and look at compliance dashboards. In a real conflict, an audit checklist doesn't stop a supply chain injection. This session breaks down a bare-metal execution architecture that treats the entire stack—from foreign-manufactured silicon up to userland applications—as actively hostile. This technical briefing introduces an end-to-end architecture designed to enforce system integrity in zero-isolation, multi-tenant environments where infrastructure is fundamentally unverified. We examine the structural implementation of the Decentralized Cryptographic Attestation Protocol (DCAP)—a system that decouples raw code execution from platform security dependencies. We will map out a deployment pipeline built on multi-tiered, segregated subnets designed to handle code from the open wilderness up to Impact Level 5 boundaries. The layout uses a dirty ingestion engine for public mirrors, an isolated scanning zone, and a completely stateless, network-isolated build sandbox driven by the Nix methodology. The objective is to demonstrate that strict mathematical proof and absolute build determinism can make physical infrastructure isolation requirements, and the hostility of the hardware itself, less relevant to operational safety.