+AI & Autonomous Technologies Event Logging

AI & Autonomous Technologies Event Logging

Description

Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities at a minimum provide:
(1) Start date, start time, end date and end time for each use;
(2) Database(s) against which input data has been checked by the system;
(3) Input data for which the search has led to a match; and
(4) Identification of individual(s) involved in the verification of the results.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Enable basic logging on AI/ML systems

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Configure event logging on AI systems
∙ Define log retention periods

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Formal AI event logging policy
∙ Centralized log collection

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ SIEM integration for AI system logs
∙ Defined logging standards for AI platforms

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Enterprise SIEM platform
∙ Standardized AI event logging schema
∙ Automated alerting for anomalous AI events

SCR-CMM

Level 0 Not Performed

Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.

Level 1 Performed Informally

Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control and risk assessments).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.

Level 2 Planned Tracked

Artificial Intelligence and Autonomous Technology (AAT) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are documented and maintained by process owners.
▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.

Level 3 Well Defined

Artificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls).
▪ An implemented and operational capability exists to ensure AAT system event logging capabilities at a minimum provide:
(1) Start date, start time, end date and end time for each use;
(2) Database(s) against which input data has been checked by the system;
(3) Input data for which the search has led to a match; and
(4) Identification of individual(s) involved in the verification of the results.

Level 4 Quantitatively Controlled

Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.

Level 5 Continuously Improving

Utilize SCR-CMM Level 3 or Level 4 (if available) criteria definitions:
▪ There are no defined Level 5 criteria, since it is reasonable to assume a continuously-improving process is not necessary to operationalize this control.
▪ Level 5 capabilities should be considered “world-class” where the control builds on Level 4 capabilities, but are continuously improving through Artificial Intelligence (AI) and/or Machine Learning (ML) technologies.
▪ While it may be possible to develop responsive capabilities for this control through the use of AI and/or ML technologies, the criteria would be organization-specific to define.

1. Apžvalga

Pavadinimas Standartas

1.1 Nuorodos

1.2 Nustatyti reikalavimai

1.3 Susiję teisės aktai

2. Nustatyti reikalavimai

Reikalavimai
Šaltinis Reikalavimas

3. Susiję teisės aktai

Teisės aktai
Šaltinis Reguliavimas
EULAW 12 straipsnis Registravimas
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EULAW 12 straipsnis Registravimas
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EULAW 12 straipsnis Registravimas
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EULAW 12 straipsnis Registravimas
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EULAW 12 straipsnis Registravimas
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EULAW 16 straipsnis Didelės rizikos DI sistemų tiekėjų pareigos

16 straipsnis

Didelės rizikos DI sistemų tiekėjų pareigos

Didelės rizikos DI sistemų tiekėjai:

a) 

užtikrina, kad jų didelės rizikos DI sistemos atitiktų 2 skirsnyje nustatytus reikalavimus;

b) 

ant didelės rizikos DI sistemos arba, jei to padaryti neįmanoma, ant jos pakuotės arba prie jos pridedamuose dokumentuose atitinkamai nurodo savo pavadinimą, registruotą prekybinį pavadinimą arba registruotą prekių ženklą ir adresą, kuriuo su jais galima susisiekti;

c) 

įdiegia 17 straipsnio reikalavimus atitinkančią kokybės valdymo sistemą;

d) 

saugo 18 straipsnyje nurodytus dokumentus;

e) 

saugo savo didelės rizikos DI sistemų automatiškai generuojamus žurnalus, jei tik tie žurnalai yra jų žinioje, kaip nurodyta 19 straipsnyje;

f) 

užtikrina, kad prieš pateikiant rinkai arba pradedant naudoti didelės rizikos DI sistemą būtų atliekama atitinkama jos atitikties vertinimo procedūra, kaip nurodyta 43 straipsnyje;

g) 

parengia ES atitikties deklaraciją pagal 47 straipsnį;

h) 

siekdami parodyti, kad jų didelės rizikos DI sistemos atitinka šio reglamento reikalavimus, pagal 48 straipsnį jas paženklina CE ženklu arba, jei to padaryti neįmanoma, paženklina jos pakuotę arba prie jos pridedamus dokumentus;

i) 

vykdo 49 straipsnio 1 dalyje nurodytas registravimo pareigas;

j) 

imasi būtinų taisomųjų veiksmų ir teikia informaciją, kaip reikalaujama 20 straipsnyje;

k) 

nacionalinės kompetentingos institucijos pagrįstu prašymu įrodo, kad didelės rizikos DI sistema atitinka 2 skirsnyje nustatytus reikalavimus;

l) 

užtikrina, kad didelės rizikos DI sistema atitiktų prieinamumo reikalavimus pagal direktyvas (ES) 2016/2102 ir (ES) 2019/882.

EULAW 26 straipsnis Didelės rizikos DI sistemų diegėjų pareigos
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Susietos užduotys

Saitai
Saito tipas Užduotis
is related to Annual
is related to relative Control Weighting = 07
is related to Process
is related to Protect
is related to SCRM Focus Tier 2 OPERATIONAL
blocks Loss of Accountability / Attribution
blocks Regulatory / Legal / Contractual Financial Liability
blocks Fraud / Theft / Direct Financial Loss
blocks Uncontrolled Internal Security / Privacy Exposure
blocks Lack of oversight of internal controls
blocks Inability to Demonstrate Due Diligence / Due Care
blocks Unreliable Assurance / Decision Information
blocks Loss of Investigative / Evidentiary Capability
blocks Delayed Containment / Increased Incident Impact
blocks Incident Persistence / Recurrence
blocks Incident Response / Recovery Cost
blocks Undetected / Delayed Detection of Adverse Activity
blocks AI Output / Decision Integrity Failure
blocks AI Data Confidentiality / Integrity / Provenance Loss
blocks Unauthorized / Harmful Autonomous Action
blocks Unintended or Unsafe Technology Behavior
blocks AI Bias / Discriminatory Outcome
blocks Loss of Authenticity / Provenance
blocks Privacy Harm / Unauthorized Processing
blocks Drought & Water Shortage
blocks Earthquakes
blocks Fire & Wildfires
blocks Floods
blocks Hurricanes & Tropical Storms
blocks Landslides & Debris Flow
blocks Pandemic (Disease) Outbreaks
blocks Severe Weather
blocks Space Weather
blocks Thunderstorms & Lightning
blocks Tornadoes
blocks Tsunamis
blocks Volcanoes
blocks Winter Storms & Extreme Cold
blocks Malicious Cyber Activity
blocks Utility Service Disruption
blocks Dysfunctional Management Practices
blocks Human Error
blocks Technical / Mechanical Failure
blocks Statutory / Regulatory / Contractual Change
blocks Data Quality Degradation / Data Poisoning
blocks Artificial Intelligence & Autonomous Technologies (AAT) System Failure or Unintended Behavior
blocks Fraud, Corruption and/or Intentional Criminal Conduct
blocks Conflict of Interest (COI) / Undue Influence / Insider Misconduct
blocks Product Defect / Design Failure
blocks Infrastructure Failure / Degradation
blocks Adversarial Artificial Intelligence (AI) Attack
is blocked by AAT-36.8 AI & Autonomous Technologies Event Logging – Assessment Procedure
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