Securing Big Data in the Age of Artificial Intelligence
Explore challenges and solutions for securing big data in AI, including hardware support, federated learning, and privacy-preserving techniques for data science and machine learning.
Guardians of the Dataverse - Securing the AI Supply and Data Chain
Explore strategies to secure AI/ML and Big Data pipelines, leveraging insights from NIST SP 800-204D and CNCF projects to protect critical AI workflows and sensitive data.
Securing the Spark Fire Hose - 2016
Learn to secure Apache Spark in big data analytics. Explore code and configuration security, data protection strategies, and integration with common technologies to safeguard critical information throughout its lifecycle.
Big Problems with Big Data - Hadoop Interfaces Security
Explore Hadoop interfaces security challenges and solutions in big data environments, focusing on potential vulnerabilities and best practices for robust protection.
Spark Over a Mesos Secured Productive Environment
Explore advanced Spark and Mesos integration for secure, isolated Big Data environments. Learn to enhance protection, manage secrets, and implement network solutions in enterprise-level deployments.
Hadoop Safari: Hunting for Vulnerabilities
Explore Hadoop security vulnerabilities, attack vectors, and tools for accessing data in Big Data clusters. Learn about design flaws and practical techniques to exploit weaknesses in Hadoop infrastructure.
Securing Your Big Data Environment
Explore strategies for securing big data environments, focusing on Hadoop. Learn about control frameworks, data protection techniques, and effective risk management for sensitive information.
The Unbelievable Insecurity of the Big Data Stack
Explore new attack vectors in Big Data infrastructure layers, addressing the lack of security assessment methodologies and technical resources for this rapidly growing field.
Attacking & Protecting Big Data Environments
Explore techniques for securing and attacking big data environments, focusing on OOP, code execution, and security measures in distributed systems.
Big Data, Little Security - Practical Steps for Securing Big Data
Practical steps for securing big data installations, addressing challenges and vulnerabilities in velocity, variety, and volume. Explores security measures, authentication, and threat modeling.
Unpoisoned Fruit - Seeding Trust into a Growing World of Algorithmic Warfare
Exploración de los desafíos éticos y de seguridad en la inteligencia artificial y el aprendizaje automático, enfocándose en la necesidad de transparencia y confianza en los sistemas algorítmicos para prevenir conflictos y desastres humanitarios.
High Fidelity Data Reduction for Big Data Security Dependency Analyses
Explores data reduction techniques for big data security dependency analyses, focusing on expendable dependencies, controlled loss, and domain knowledge to improve efficiency while maintaining accuracy.
Hadoop Safari - Hunting for Vulnerabilities
Explore Hadoop security vulnerabilities and attack vectors in Big Data environments. Learn practical techniques to access data lakes and exploit weaknesses in cluster infrastructures.
Big Hugs for Big Data
Explore the intersection of big data and security with insights on privacy, ethics, and risk management in the digital age.
Analyzing Pwned Passwords with Apache Spark
Learn to analyze compromised passwords using Apache Spark, exploring data visualization, password policies, and big data security challenges for improved cybersecurity practices.
Securing Apache Spark Big Data Operations: Threats, Best Practices, and Pragmatic Steps
Explore Apache Spark security best practices, threat modeling, and practical steps to safeguard big data operations in various environments.
A Holistic Approach to Securing Spark-Based Data Engineering
Learn to secure Apache Spark-based data engineering applications. Explore security best practices, identify threats, prioritize requirements, and implement practical steps for Kubernetes and object storage environments.
The most dangerous lie AI keeps repeating | Karen Colbert | TEDxBellarmineU
This talk challenges the dominant narrative that artificial intelligence is neutral, objective, and inevitable. Drawing on lived experience in education, engineering, and data science, Karen Colbert reveals how AI systems often reproduce historical inequities because they are built on incomplete dat
Black Hat Europe 2024
Black Hat Europe 2024