Security

21 techniques

Protecting AI systems from malicious attacks and unauthorized access.

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All techniques

21 techniques
GoalsModelsData TypesDescription
Homomorphic Encryption
Algorithmic
Architecture/linear Models
Architecture/model Agnostic
+4
Any
Homomorphic encryption allows computation on encrypted data without decrypting it first, producing encrypted results...
Cross-validation
Algorithmic
Architecture/model Agnostic
Paradigm/supervised
+2
Any
Cross-validation evaluates model performance and robustness by systematically partitioning data into multiple subsets...
Internal Review Boards
Process
Architecture/model Agnostic
Requirements/black Box
Any
Internal Review Boards (IRBs) provide independent, systematic evaluation of AI/ML projects throughout their lifecycle to...
Red Teaming
Procedural
Architecture/model Agnostic
Requirements/black Box
Any
Red teaming is a structured adversarial evaluation process in which a dedicated team systematically probes an AI/ML...
Human-in-the-Loop Safeguards
Process
Architecture/model Agnostic
Requirements/black Box
Any
Human-in-the-loop safeguards establish systematic checkpoints where human experts review, validate, or override AI/ML...
Confidence Thresholding
Algorithmic
Architecture/model Agnostic
Requirements/black Box
+1
Any
Confidence thresholding creates decision boundaries based on model uncertainty scores, routing predictions into...
Runtime Monitoring and Circuit Breakers
Algorithmic
Architecture/model Agnostic
Requirements/black Box
Any
Runtime monitoring and circuit breakers establish continuous surveillance of AI/ML systems in production, tracking...
Model Cards
Documentation
Architecture/model Agnostic
Requirements/black Box
Any
Model cards are standardised documentation frameworks that systematically document machine learning models through...
Datasheets for Datasets
Documentation
Architecture/model Agnostic
Requirements/black Box
Any
Datasheets for datasets establish comprehensive documentation standards for datasets, systematically recording creation...
MLflow Experiment Tracking
Process
Architecture/model Agnostic
Requirements/black Box
Any
MLflow is an open-source platform that tracks machine learning experiments by automatically logging parameters, metrics,...
Data Version Control
Process
Architecture/model Agnostic
Requirements/black Box
Any
Data Version Control (DVC) is a Git-like version control system specifically designed for machine learning data, models,...
Model Development Audit Trails
Procedural
Architecture/model Agnostic
Requirements/black Box
Any
Model development audit trails create comprehensive, immutable records of all decisions, experiments, and changes...
Adversarial Training Evaluation
Testing
Architecture/model Agnostic
Architecture/neural Networks
+1
Any
Adversarial training evaluation assesses whether models trained with adversarial examples have genuinely improved...
API Usage Pattern Monitoring
Algorithmic
Architecture/model Agnostic
Requirements/black Box
Any
API usage pattern monitoring analyses AI model API usage to detect anomalies and generate evidence of secure operation....
Data Poisoning Detection
Algorithmic
Architecture/model Agnostic
Requirements/white Box
+1
Any
Data poisoning detection identifies malicious training data designed to compromise model behaviour. This technique...
Jailbreak Resistance Testing
Testing
Architecture/neural Networks/transformer/llm
Requirements/black Box
Text
Jailbreak resistance testing evaluates LLM defences against techniques that bypass safety constraints. This involves...
Model Extraction Defence Testing
Testing
Architecture/model Agnostic
Requirements/black Box
Any
Model extraction defence testing evaluates protections against attackers who attempt to steal model functionality by...
Multi-Agent System Testing
Testing
Architecture/model Agnostic
Requirements/black Box
Any
Multi-agent system testing evaluates safety and reliability of systems where multiple AI agents interact, coordinate, or...
Membership Inference Attack Testing
Testing
Architecture/model Agnostic
Requirements/black Box
Any
Membership inference attack testing evaluates whether adversaries can determine if specific data points were included in...
Model Watermarking and Theft Detection
Algorithmic
Architecture/model Agnostic
Requirements/black Box
Any
Model watermarking and theft detection techniques protect AI systems from unauthorised replication by embedding...
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