
Explore how the ELISA Project facilitates Linux adoption in safety-critical systems, enhancing reliability and security for critical applications across industries.

Explore ACRN Hypervisor's innovative approach to consolidating real-time and HMI systems, addressing challenges in industrial automation with virtualization and strict real-time performance requirements.

Explore the resurgence of cyber-physical offensive capabilities and their implications for modern security landscapes in this insightful presentation by Daniel Kapellmann Zafra.

Explore CNNs for industrial visual inspection, learning how to train robust networks with limited datasets using PLS-inspired constraints. Gain insights for effective implementation in downstream processes.

Explore ICS-specific OSINT techniques and freely available data used by adversaries in attacks. Learn to decrease attack surface and increase adversary friction in industrial control systems.

Explore vulnerabilities in PLCs, learn discovery methods, and see how minor flaws can lead to device takeover. Gain insights into industrial control system security and potential exploits.

Comprehensive analysis of recent SCADA vulnerabilities in industrial control systems, covering root causes, attack vectors, consequences, and remediation strategies for critical infrastructure security.

Explore vulnerabilities in ICS-SCADA systems for critical infrastructure, comparing IT and OT security approaches. Learn from an expert about protecting industrial control systems against sophisticated cyber attacks.

Análisis del malware Industroyer, diseñado para atacar redes eléctricas. Se explora su funcionamiento, impacto en Ucrania y potenciales amenazas globales para infraestructuras críticas.

Presentación de vulnerabilidades en PLC de Schneider-Electric, demostrando vectores de ataque y herramientas para automatizar procesos maliciosos en infraestructuras críticas industriales.

Introducción al modelo de seguridad industrial y simulación de un ataque en tiempo real a dispositivos ICS. Descubre cómo identificar y explotar vulnerabilidades en sistemas de control industrial.

Explore vulnerabilities in industrial robots, uncovering potential security risks and attack vectors. Learn about the implications for safety and productivity in automated manufacturing environments.

Exploración de la captura de amenazas en entornos industriales, abordando tecnología operacional, ciberseguridad en ICS, honeypots y estrategias para proteger sistemas industriales.

Explore unconstrained code execution on Siemens S7 PLCs, revealing bootloader vulnerabilities and security implications. Learn about the special access feature and its potential for exploitation or forensic use.

Explore Zero Trust concepts for Industrial Control Systems, addressing vulnerabilities and improving cybersecurity readiness across IT and OT domains for enhanced threat response.

Insights from industry leaders on establishing effective product security programs, covering design, awareness, and response strategies for major cyber threats.

Experts from SANS Institute discuss the most dangerous new attack techniques, including hardware attacks, big data weaponization, crypto mining, ICS safety threats, and cloud breaches, offering insights on defeating these evolving threats.

Analysis of INCONTROLLER: a rare and dangerous state-sponsored malware targeting industrial control systems, with focus on its components, attack scenarios, and implications for cybersecurity professionals.

Explore designing implants and payloads for ICS embedded devices, covering discovery, attack design, and damage stages in cyber-physical attacks on industrial control systems.

Explore vulnerabilities in PLCs, focusing on discovery methods and how combining minor flaws can lead to device takeover. Learn about SNMP exploitation, memory manipulation, and firmware modification.

Explore DYODE, a low-cost DIY data diode for securing Industrial Control Systems. Learn about its development, components, and applications in file transfer, Modbus data, and remote debugging.