Security
26 techniques
Protecting AI systems from malicious attacks and unauthorized access.
26 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Homomorphic Encryption | Algorithmic | Architecture/linear Models Architecture/neural Networks/feedforward +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 involves systematic adversarial testing of AI/ML systems by dedicated specialists who attempt to identify... | ||
| Anomaly Detection | Algorithmic | Architecture/model Agnostic Requirements/black Box +1 | Any | Anomaly detection identifies unusual behaviours, inputs, or outputs that deviate significantly from established normal... | ||
| 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,... | ||
| Automated Documentation Generation | Algorithmic | Architecture/model Agnostic Requirements/black Box | Any | Automated documentation generation creates and maintains up-to-date documentation using various methods including... | ||
| 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 Robustness Testing | Testing | Architecture/model Agnostic Architecture/neural Networks +2 | Image Text Tabular | Adversarial robustness testing evaluates model resilience against intentionally crafted inputs designed to cause... | ||
| 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... | ||
| Safety Guardrails | Algorithmic | Architecture/model Agnostic Requirements/black Box | Text | Safety guardrails apply real-time content moderation and safety constraints during deployment, generating evidence of... | ||
| 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... |
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