+Quality Management System (QMS)
|
Quality Management System (QMS)
Description
Mechanisms exist to govern a Quality Management System (QMS) to ensure security, compliance and resilience processes conform with applicable statutory, regulatory and/or contractual obligations.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Document basic quality checkpoints for security processes
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Written quality standards for key security processes
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal QMS procedures for security processes
∙ Internal quality reviews
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ ISO 9001-aligned QMS for security operations
∙ Formal QA function
∙ Periodic internal audits
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ ISO 9001 certified QMS
∙ Dedicated quality assurance team
∙ Continuous process improvement program
∙ Integrated QMS platform
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
Cybersecurity & Data Protection Governance (GOV) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with GOV domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ Governance-related activities are decentralized (e.g., a localized/regionalized function) and uses non-standardized methods to implement secure, resilient and compliant practices.
▪ No formal Governance, Risk & Compliance (GRC) team exists. GRC roles are assigned to existing IT/cybersecurity personnel.
▪ Cybersecurity and data protection governance is informally assigned as an additional duty to existing IT/cybersecurity personnel.
▪ Unstructured review of the cybersecurity and/or data privacy program is performed on an annual basis.
▪ Administrative processes require all employees and contractors to apply cybersecurity and data protection principles in their daily work (e.g., policies & standards).
Level 2 Planned Tracked
SCR-CMM Level 2 criteria definitions are not available for this control:
▪ A reasonable person would conclude a well-defined and standardized process is required.
▪ At this level of maturity, the “requirements-driven” nature of performing the control is focused on a localized and/or regionalized implementation, not uniform and consistent across the organization.
▪ Requirements are narrowly scoped for applicability and are primarily derived from compliance obligations (e.g., laws, regulations and contracts).
Level 3 Well Defined
Cybersecurity & Data Protection Governance (GOV) 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 GOV 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 GOV domain capabilities are well-documented and kept current by process owners.
▪ The entity's GRC team, or similar function, is appropriately staffed and supported to implement and maintain GOV 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).
▪ Technology is leveraged to enhance the efficiency and accuracy of governance, risk management and compliance operations (e.g., GRC platform).
▪ An implemented and operational capability exists to govern a Quality Management System (QMS) to ensure security, compliance and resilience processes conform with applicable statutory, regulatory and/or contractual obligations.
Level 4 Quantitatively Controlled
Cybersecurity & Data Protection Governance (GOV) capabilities, in addition to being standardized across the entity and centrally managed to ensure consistency across Technology Assets, Applications, Services and/or Data (TAASD), efforts are metrics driven to provide sufficient insight for decision makers to predict optimal performance, ensure continued operations and/or identify areas for improvement. Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational.
▪ Metrics reporting includes quantitative analysis of Key Performance Indicators (KPIs).
▪ Metrics reporting includes quantitative analysis of Key Risk Indicators (KRIs).
▪ Scope of metrics, KPIs and KRIs covers organization-wide cybersecurity and data protection controls, including functions performed by third-parties.
▪ Organizational leadership maintains a formal process to objectively review and respond to metrics, KPIs and KRIs (e.g., monthly or quarterly review).
▪ Based on metrics analysis, process improvement recommendations are submitted for review and are handled in accordance with change control processes.
▪ Business and technical stakeholders are involved in reviewing and approving proposed changes to evolve capabilities.
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. Overview
1.1 References
1.2 Identified Requirements
1.3 Related Regulations
2. Identified Requirements
Requirements
| Source |
Requirement |
3. Related Regulations
Regulations
| Source |
Regulation |
|
EULAW
|
Article 16 Obligations of providers of high-risk AI systems
Article 16
Obligations of providers of high-risk AI systems
Providers of high-risk AI systems shall:
|
(a)
|
ensure that their high-risk AI systems are compliant with the requirements set out in Section 2;
|
|
(b)
|
indicate on the high-risk AI system or, where that is not possible, on its packaging or its accompanying documentation, as applicable, their name, registered trade name or registered trade mark, the address at which they can be contacted;
|
|
(c)
|
have a quality management system in place which complies with Article 17;
|
|
(d)
|
keep the documentation referred to in Article 18;
|
|
(e)
|
when under their control, keep the logs automatically generated by their high-risk AI systems as referred to in Article 19;
|
|
(f)
|
ensure that the high-risk AI system undergoes the relevant conformity assessment procedure as referred to in Article 43, prior to its being placed on the market or put into service;
|
|
(g)
|
draw up an EU declaration of conformity in accordance with Article 47;
|
|
(h)
|
affix the CE marking to the high-risk AI system or, where that is not possible, on its packaging or its accompanying documentation, to indicate conformity with this Regulation, in accordance with Article 48;
|
|
(i)
|
comply with the registration obligations referred to in Article 49(1);
|
|
(j)
|
take the necessary corrective actions and provide information as required in Article 20;
|
|
(k)
|
upon a reasoned request of a national competent authority, demonstrate the conformity of the high-risk AI system with the requirements set out in Section 2;
|
|
(l)
|
ensure that the high-risk AI system complies with accessibility requirements in accordance with Directives (EU) 2016/2102 and (EU) 2019/882.
|
|
|
EULAW
|
Article 17 Quality management system
Article 17
Quality management system
1. Providers of high-risk AI systems shall put a quality management system in place that ensures compliance with this Regulation. That system shall be documented in a systematic and orderly manner in the form of written policies, procedures and instructions, and shall include at least the following aspects:
|
(a)
|
a strategy for regulatory compliance, including compliance with conformity assessment procedures and procedures for the management of modifications to the high-risk AI system;
|
|
(b)
|
techniques, procedures and systematic actions to be used for the design, design control and design verification of the high-risk AI system;
|
|
(c)
|
techniques, procedures and systematic actions to be used for the development, quality control and quality assurance of the high-risk AI system;
|
|
(d)
|
examination, test and validation procedures to be carried out before, during and after the development of the high-risk AI system, and the frequency with which they have to be carried out;
|
|
(e)
|
technical specifications, including standards, to be applied and, where the relevant harmonised standards are not applied in full or do not cover all of the relevant requirements set out in Section 2, the means to be used to ensure that the high-risk AI system complies with those requirements;
|
|
(f)
|
systems and procedures for data management, including data acquisition, data collection, data analysis, data labelling, data storage, data filtration, data mining, data aggregation, data retention and any other operation regarding the data that is performed before and for the purpose of the placing on the market or the putting into service of high-risk AI systems;
|
|
(g)
|
the risk management system referred to in Article 9;
|
|
(h)
|
the setting-up, implementation and maintenance of a post-market monitoring system, in accordance with Article 72;
|
|
(i)
|
procedures related to the reporting of a serious incident in accordance with Article 73;
|
|
(j)
|
the handling of communication with national competent authorities, other relevant authorities, including those providing or supporting the access to data, notified bodies, other operators, customers or other interested parties;
|
|
(k)
|
systems and procedures for record-keeping of all relevant documentation and information;
|
|
(l)
|
resource management, including security-of-supply related measures;
|
|
(m)
|
an accountability framework setting out the responsibilities of the management and other staff with regard to all the aspects listed in this paragraph.
|
2. The implementation of the aspects referred to in paragraph 1 shall be proportionate to the size of the provider’s organisation. Providers shall, in any event, respect the degree of rigour and the level of protection required to ensure the compliance of their high-risk AI systems with this Regulation.
3. Providers of high-risk AI systems that are subject to obligations regarding quality management systems or an equivalent function under relevant sectoral Union law may include the aspects listed in paragraph 1 as part of the quality management systems pursuant to that law.
4. For providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services law, the obligation to put in place a quality management system, with the exception of paragraph 1, points (g), (h) and (i) of this Article, shall be deemed to be fulfilled by complying with the rules on internal governance arrangements or processes pursuant to the relevant Union financial services law. To that end, any harmonised standards referred to in Article 40 shall be taken into account.
|
Linked Issues
- Secure Controls Framework -
"The SCF is the Common Controls Framework™ (CCF), the world's most comprehensive cybersecurity and data privacy metaframework - it is also free to use. The entire concept is building secure, compliant and resilient capabilities in the most efficient and cost-effective manner possible.
The SCF is more than just a unified control catalog, since its included content creates a playbook for Governance, Risk & Compliance (GRC) capabilities. Used globally by organizations of every size, the SCF is a robust and scalable solution for security, compliance and resilience controls. As a comprehensive security framework, the SCF maps 1,400+ controls across 200+ laws, regulations, and industry frameworks so you can implement once and comply everywhere.
Like it or not, cybersecurity is a protracted war on an asymmetric battlefield, where the threats are everywhere and as defenders we have to make the effort to work together to help improve cybersecurity and data privacy practices, since we all suffer when massive data breaches occur or when cyber attacks have physical impacts. Hackers share information on attack methods with other hackers, so why shouldn’t the good guys share information on how to best protect an organization? We decided to take action and make a difference, since we feel it is too important to wait for someone else to fix the problems that exist.
The SCF is made up of volunteers, mainly specialists within the cybersecurity profession, who focus on GRC and the cybersecurity side of data privacy. These are auditors, engineers, architects, incident responders, consultants and other specialists who live and breathe these topics on a daily basis. The end product is "expert-derived content" that makes up the SCF." https://securecontrolsframework.com/
Terms & Conditions
The SCF End User License Agreement (EULA) governs the use of the Secure Controls Framework® (SCF) under the Creative Commons Attribution-No Derivatives 4.0 International Public License.
|