| {"slug":"abistemplate","title":"Automated Biometric Identification System (ABIS)","definition":"System for large-scale biometric matching and identification using algorithms and databases.","related":["matching"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is an Automated Biometric Identification System (ABIS)?","answer":"An ABIS is a system that automates large-scale biometric matching and identification using algorithms and centralized databases."},{"question":"How does ABIS improve biometric matching?","answer":"ABIS leverages advanced algorithms to process and compare biometric data at scale, reducing manual verification and improving throughput."},{"question":"What are common applications of ABIS?","answer":"Typical use cases include criminal investigations, border security, and large-scale identity verification in government programs."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/abistemplate.md","canonicalPath":"/glossary/abistemplate","apiPath":"/api/glossary/abistemplate"}} | |
| {"slug":"consent","title":"Consent","definition":"Voluntary agreement by a person for their personal data to be used for specific purposes.","related":["gdpr"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What does consent mean in data privacy?","answer":"Consent is a person’s voluntary and informed agreement for their personal data to be collected, processed, and used for specific purposes."},{"question":"Why is consent important for biometric data?","answer":"Biometric data is sensitive; obtaining consent ensures compliance with privacy laws and respect for individual autonomy."},{"question":"How can organizations obtain valid consent?","answer":"Valid consent requires clear information, unambiguous opt-in mechanisms, and allows individuals to withdraw consent at any time."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/consent.md","canonicalPath":"/glossary/consent","apiPath":"/api/glossary/consent"}} | |
| {"slug":"deep-learning","title":"Deep Learning","definition":"Subset of machine learning using neural networks with multiple layers to model complex data representations.","related":["facial-recognition"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is deep learning?","answer":"Deep learning is a subset of machine learning that uses neural networks with multiple layers to model complex patterns and representations."},{"question":"How is deep learning used in biometric systems?","answer":"Techniques like convolutional neural networks (CNNs) extract high-dimensional features from biometric data (e.g., face, fingerprint) to improve recognition accuracy."},{"question":"Why is deep learning important for biometric matching?","answer":"Deep learning models automatically learn discriminative features, reducing manual feature engineering and enhancing performance across varied conditions."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/deep-learning.md","canonicalPath":"/glossary/deep-learning","apiPath":"/api/glossary/deep-learning"}} | |
| {"title":"Equal Error Rate (EER)","slug":"eer","definition":"A single operating point where the false match rate equals the false non‑match rate. Lower EER generally indicates better discriminative performance for a matcher on a given dataset.","related":["facial-recognition","fingerprint-recognition","iris-recognition","multimodal-biometrics"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/eer.md","canonicalPath":"/glossary/eer","apiPath":"/api/glossary/eer"}} | |
| {"slug":"eidas","title":"eIDAS","definition":"EU regulation on electronic identification and trust services for secure electronic transactions.","related":["digital-identity"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is eIDAS regulation?","answer":"The eIDAS Regulation is an EU framework for electronic identification and trust services, setting standards for secure online transactions and legally recognized electronic signatures."},{"question":"How does eIDAS impact digital identity services?","answer":"eIDAS ensures cross-border interoperability of digital identity schemes, enabling secure authentication and electronic signatures across EU member states."},{"question":"What are the assurance levels defined by eIDAS?","answer":"eIDAS defines assurance levels (low, substantial, high) based on the rigor of identity proofing and authentication methods required for different security needs."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/eidas.md","canonicalPath":"/glossary/eidas","apiPath":"/api/glossary/eidas"}} | |
| {"title":"Failure to Acquire (FTA)","slug":"failure-to-acquire","definition":"The proportion of attempts where a usable biometric sample cannot be captured (e.g., sensor or user issues). FTA reduces overall system throughput and may bias evaluations if not accounted for.","related":["fingerprint-recognition","facial-recognition","iris-recognition","behavioral-biometrics"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/failure-to-acquire.md","canonicalPath":"/glossary/failure-to-acquire","apiPath":"/api/glossary/failure-to-acquire"}} | |
| {"title":"Failure to Enroll (FTE)","slug":"failure-to-enroll","definition":"The proportion of subjects who cannot be enrolled due to poor quality or insufficient data. High FTE indicates capture or process issues that limit coverage of the intended population.","related":["fingerprint-recognition","facial-recognition","iris-recognition","abis-dedup"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/failure-to-enroll.md","canonicalPath":"/glossary/failure-to-enroll","apiPath":"/api/glossary/failure-to-enroll"}} | |
| {"slug":"fido","title":"FIDO Alliance","definition":"Industry consortium promoting standards for strong authentication like U2F and FIDO2.","related":["u2f"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is the FIDO Alliance?","answer":"The FIDO Alliance is an industry consortium that develops open authentication standards to reduce reliance on passwords and enhance security with strong, phishing-resistant methods."},{"question":"What authentication protocols does FIDO support?","answer":"FIDO supports protocols like U2F (Universal 2nd Factor) and FIDO2, which use public key cryptography and hardware or platform authenticators."},{"question":"How does FIDO improve online authentication security?","answer":"By replacing shared secrets with unique cryptographic keys tied to a user’s device and requiring user presence, FIDO mitigates phishing and credential theft."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/fido.md","canonicalPath":"/glossary/fido","apiPath":"/api/glossary/fido"}} | |
| {"title":"FMR and FNMR","slug":"fmr-fnmr","definition":"FMR (False Match Rate) is the proportion of impostor comparisons incorrectly accepted; FNMR (False Non‑Match Rate) is the proportion of genuine comparisons incorrectly rejected. They trade off with the decision threshold.","related":["facial-recognition","fingerprint-recognition","iris-recognition"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/fmr-fnmr.md","canonicalPath":"/glossary/fmr-fnmr","apiPath":"/api/glossary/fmr-fnmr"}} | |
| {"slug":"gdpr","title":"General Data Protection Regulation (GDPR)","definition":"EU regulation enforcing data protection and privacy for individuals within the European Union.","related":["privacy"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is the GDPR?","answer":"The General Data Protection Regulation (GDPR) is an EU regulation that governs the collection, processing, and protection of personal data for individuals within the European Union."},{"question":"How does GDPR treat biometric data?","answer":"Under GDPR, biometric data is classified as sensitive personal data, requiring explicit consent, strict security measures, and legal justification for processing."},{"question":"What rights do individuals have under GDPR?","answer":"GDPR grants rights such as access, rectification, erasure, data portability, and the right to object to processing of personal data."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/gdpr.md","canonicalPath":"/glossary/gdpr","apiPath":"/api/glossary/gdpr"}} | |
| {"title":"Identification vs Verification","slug":"identification-vs-verification","definition":"Identification answers ‘who is this?’ via 1:N search against a gallery. Verification answers ‘is this person who they claim?’ via 1:1 comparison between a probe and a claimed identity’s reference.","related":["abis-dedup","facial-recognition","fingerprint-recognition","passkeys-webauthn"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/identification-vs-verification.md","canonicalPath":"/glossary/identification-vs-verification","apiPath":"/api/glossary/identification-vs-verification"}} | |
| {"slug":"identity-proofing","title":"Identity Proofing","definition":"Process of verifying that a person is who they claim to be, often using ID documents and biometric checks.","related":["digital-identity"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is identity proofing?","answer":"Identity proofing is the process of verifying that a person is who they claim to be, often using documents, biometric checks, and trusted data sources."},{"question":"Why is identity proofing essential for digital services?","answer":"It prevents identity fraud by ensuring only legitimate users can enroll and access services, supporting security and regulatory compliance."},{"question":"Which methods are used for identity proofing?","answer":"Common methods include document verification, facial recognition with liveness detection, and database checks against authoritative records."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/identity-proofing.md","canonicalPath":"/glossary/identity-proofing","apiPath":"/api/glossary/identity-proofing"}} | |
| {"slug":"matching","title":"Biometric Matching","definition":"Comparing a biometric sample against stored templates to verify or identify an individual.","related":["abistemplate","template"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is biometric matching?","answer":"Biometric matching compares a captured biometric sample against stored templates to verify or identify an individual based on similarity scores."},{"question":"What are verification and identification in biometric matching?","answer":"Verification (1:1) confirms a claimed identity, while identification (1:N) searches a database to find a matching identity without a prior claim."},{"question":"What factors influence matching accuracy?","answer":"Accuracy depends on sample quality, sensor reliability, algorithm robustness, environmental conditions, and threshold settings."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/matching.md","canonicalPath":"/glossary/matching","apiPath":"/api/glossary/matching"}} | |
| {"slug":"multi-factor-authentication","title":"Multi-Factor Authentication (MFA)","definition":"Authentication method requiring two or more verification factors, such as something you know and something you are.","related":["u2f","fido"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is multi-factor authentication (MFA)?","answer":"MFA is an authentication method requiring two or more verification factors, such as something you know (password), something you have (token), and something you are (biometric)."},{"question":"How does MFA improve security?","answer":"By combining independent factors, MFA reduces the risk of unauthorized access if one factor is compromised, strengthening overall protection."},{"question":"What are common MFA examples?","answer":"Examples include password plus SMS OTP, hardware tokens with PIN, smartphone push notifications, and biometric factors like fingerprint or face recognition."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/multi-factor-authentication.md","canonicalPath":"/glossary/multi-factor-authentication","apiPath":"/api/glossary/multi-factor-authentication"}} | |
| {"slug":"nist-frvt","title":"NIST Face Recognition Vendor Test (FRVT)","definition":"A series of evaluations by NIST to benchmark face recognition algorithms under controlled and uncontrolled conditions.","related":["facial-recognition"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is NIST FRVT?","answer":"The NIST Face Recognition Vendor Test (FRVT) is a benchmarking program evaluating face recognition algorithm performance under various conditions."},{"question":"How does NIST FRVT assess face recognition?","answer":"FRVT measures accuracy, speed, and interoperability by testing algorithms on standard datasets and reporting metrics like false match and non-match rates."},{"question":"Why are NIST FRVT results important?","answer":"Unbiased FRVT results guide organizations in selecting reliable face recognition solutions by providing standardized performance benchmarks."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/nist-frvt.md","canonicalPath":"/glossary/nist-frvt","apiPath":"/api/glossary/nist-frvt"}} | |
| {"title":"On‑Device vs Server‑Side Matching","slug":"on-device-vs-server-matching","definition":"Design choice where biometric matching happens locally on a user’s device (with templates kept device‑bound) versus centrally on a server. On‑device improves privacy and reduces breach scope; server‑side can enable centralized management and large‑scale search (1:N).","related":["passkeys-webauthn","facial-recognition","digital-id"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/on-device-vs-server-matching.md","canonicalPath":"/glossary/on-device-vs-server-matching","apiPath":"/api/glossary/on-device-vs-server-matching"}} | |
| {"slug":"pad","title":"Presentation Attack Detection (PAD)","definition":"PAD refers to techniques used to detect artefacts (masks, photos, deepfakes) intended to spoof biometric systems.","related":["facial-recognition","fingerprint-recognition","voice-recognition","iris-recognition"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is Presentation Attack Detection (PAD)?","answer":"PAD refers to techniques used to detect and prevent spoofing attacks by verifying that a biometric sample originates from a live human rather than artificial artefacts."},{"question":"Why is PAD critical for biometric systems?","answer":"PAD ensures security by preventing attackers from using masks, photos, or deepfake videos to spoof biometric authentication."},{"question":"What methods are used for PAD?","answer":"Common methods include texture analysis, motion/liveness detection, infrared imaging for vein patterns, and challenge-response protocols."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/pad.md","canonicalPath":"/glossary/pad","apiPath":"/api/glossary/pad"}} | |
| {"slug":"privacy","title":"Privacy","definition":"The right of individuals to control the collection, use, and disclosure of their personal data.","related":["gdpr"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What does privacy mean in biometrics?","answer":"Privacy in biometrics refers to individuals’ rights to control how their biometric data is collected, processed, stored, and shared."},{"question":"How do privacy regulations protect biometric data?","answer":"Regulations like GDPR and CCPA enforce data minimization, consent requirements, and security controls for handling biometric information."},{"question":"What are best practices for ensuring biometric privacy?","answer":"Best practices include encryption of data at rest and in transit, anonymization, strict access controls, transparent policies, and user consent."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/privacy.md","canonicalPath":"/glossary/privacy","apiPath":"/api/glossary/privacy"}} | |
| {"title":"ROC and DET Curves","slug":"roc-det","definition":"Receiver Operating Characteristic (ROC) and Detection Error Tradeoff (DET) curves visualize biometric performance across thresholds. ROC plots true accept vs false accept; DET plots false reject vs false accept on normal deviate scales for readability.","related":["fmr-fnmr","facial-recognition","fingerprint-recognition","iris-recognition"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/roc-det.md","canonicalPath":"/glossary/roc-det","apiPath":"/api/glossary/roc-det"}} | |
| {"slug":"spoofing","title":"Biometric Spoofing","definition":"Attempt to deceive a biometric system by presenting artificial traits like masks or fake fingerprints.","related":["pad"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is biometric spoofing?","answer":"Biometric spoofing is the act of deceiving a biometric system by presenting fake traits like silicone fingerprints, printed face images, or masks."},{"question":"How do systems detect spoofing attacks?","answer":"Detection uses PAD techniques, liveness detection algorithms, multi-modal biometrics, and machine learning classifiers to identify artefacts."},{"question":"What are the security risks of biometric spoofing?","answer":"Successful spoofing can grant unauthorized access, compromise security, and undermine trust in biometric authentication solutions."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/spoofing.md","canonicalPath":"/glossary/spoofing","apiPath":"/api/glossary/spoofing"}} | |
| {"title":"Template Inversion","slug":"template-inversion","definition":"An attack that attempts to reconstruct a biometric sample (e.g., a face image or fingerprint) from its stored template or embedding. Strong template protection schemes aim to make inversion computationally infeasible or yield unusable reconstructions.","related":["template-protection","facial-recognition","fingerprint-recognition"],"createdAt":"2025-11-10T00:00:00.000Z","updatedAt":"2025-11-10T00:00:00.000Z","license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/template-inversion.md","canonicalPath":"/glossary/template-inversion","apiPath":"/api/glossary/template-inversion"}} | |
| {"slug":"template","title":"Biometric Template","definition":"Digital representation of biometric features extracted from a sample for matching and storage.","related":["matching"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is a biometric template?","answer":"A biometric template is a digital representation of extracted features (e.g., fingerprint minutiae or facial embeddings) used for matching and storage."},{"question":"How are biometric templates protected?","answer":"Templates are secured through encryption, hashing, cancelable biometric schemes, and secure hardware to prevent theft and misuse."},{"question":"Why use templates instead of raw biometric data?","answer":"Templates abstract away raw images, reducing storage requirements, protecting privacy, and enabling fast and secure comparisons."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/template.md","canonicalPath":"/glossary/template","apiPath":"/api/glossary/template"}} | |
| {"slug":"u2f","title":"Universal 2nd Factor (U2F)","definition":"Open authentication standard that adds a second factor using hardware tokens for stronger security.","related":["fido"],"createdAt":"2025-05-07T00:00:00.000Z","updatedAt":"2025-05-07T00:00:00.000Z","faq":[{"question":"What is Universal 2nd Factor (U2F)?","answer":"U2F is an open authentication standard by the FIDO Alliance that uses hardware tokens (USB/NFC) to provide phishing-resistant two-factor authentication."},{"question":"How does U2F prevent phishing attacks?","answer":"U2F uses origin-bound cryptographic challenge-response, ensuring tokens only authenticate legitimate websites and thwarting phishing attempts."},{"question":"Can one U2F device be used with multiple services?","answer":"Yes, U2F tokens generate unique key pairs per service, allowing secure, cross-platform authentication with a single physical device."}],"license":"CC-BY-4.0","_meta":{"dataset":"glossary","schemaVersion":"1.0.0","license":"CC-BY-4.0","sourceType":"markdown","sourcePath":"content/glossary/u2f.md","canonicalPath":"/glossary/u2f","apiPath":"/api/glossary/u2f"}} | |