Cybersecurity

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• Case Studies
  • Risk, Compliance and Regulation
    • Screening; Passenger, Luggage, & Cargo
  • Government Services
  • Defense
• Capabilities
• Cybersecurity References
• Offense - Adversarial Threats/Attacks
• Cybersecurity Frameworks, Architectures & Roadmaps
• Cybersecurity Companies/Products
• Cybersecurity: National Institute of Standards and Technology (NIST) & U.S. Department of Homeland Security (DHS)
• Cybersecurity: Evaluating & Selling
• (Artificial) Immune System
• Useful Models ...find outliers:
  • One-class Support Vector Machine (SVM)
  • Variational Autoencoder (VAE)
  • Autoencoder (AE) / Encoder-Decoder
  • Radial Basis Function Network (RBFN)
  • Bidirectional Long Short-Term Memory (BI-LSTM) with Attention Mechanism
• Detecting Malicious Requests with Keras & TensorFlow | Adam Kusey - Medium
• Best security software: How 12 cutting-edge tools tackle today's threats | CSO
• graphistry.com
• Intelligence Advanced Research Projects Activity (IARPA)Is Trying Keep Adversaries From Corrupting AI Tools ... Could cyber adversaries be training the government’s artificial intelligence tools to fail? | Jack Corrigan - Nextgov
  • TrojAI - Office of the Director of National Intelligence Office: Intelligence Advanced Research Projects Activity FedBizOpps.gov predict whether AI systems have been corrupted through so-called “Trojan attacks.”
• Adversarial Attacks on Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning
• Breaking Down the Tencent 2018 Cybersecurity Report
• Chronicle combines all the best parts of Google and X culture
• Fraud and Anomaly Detection | Chris Nicholson - A.I. Wiki pathmind
• Watch me Build a Cybersecurity Startup | Siraj Raval

Fraud Detection

• Introduction to Fraud Detection Systems | Miguel Gonzalez-Fierro, Microsoft
• AI for Health Insurance Fraud Detection – Current Applications | Niccolo Mejia