Research Division
Academic Research
An Adapted Zero-Trust Security Framework with AI-Based Anomaly Detection and Blockchain-Anchored Audit Trails for Data Acquisition Systems
M.Sc. Thesis — Istinye University, Cybersecurity Program
Zero-Trust Architecture
Session-based trust evaluation for streaming DAQ data
AI Anomaly Detection
LSTM-Autoencoder + Random Forest two-stage pipeline
Blockchain Audit Trails
Hyperledger Fabric selective event anchoring
Hypothesis Targets
H1: < 15% throughput reduction
Zero-trust overhead on DAQ throughput
H2: F1 > 0.95 detection accuracy
AI anomaly detection performance
H3: < 10ms blockchain overhead
Blockchain anchoring latency target
Affiliations
Additional Research
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