+Член 49 Дерогации в особени случаи
---+Член 49 1.
---+Член 49 2.
---+Член 49 3.
---+Член 49 4.
---+Член 49 5.
---+Член 49 6.

Член 49 Дерогации в особени случаи

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1. Преглед

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Член 49 1.

При липса на решение относно адекватното ниво на защита съгласно член 45, параграф 3 или на подходящи гаранции съгласно член 46, включително задължителни фирмени правила, предаване или съвкупност от предавания на лични данни на трета държава или международна организация се извършва само при едно от следните условия:

a) 

субектът на данните изрично е дал съгласието си за предлаганото предаване на данни, след като е бил информиран за свързаните с предаването възможни рискове за субекта на данните поради липсата на решение относно адекватното ниво на защита и на подходящи гаранции;

б) 

предаването е необходимо за изпълнението на договор между субекта на данните и администратора или за изпълнението на преддоговорни мерки, взети по искане на субекта на данните;

в) 

предаването е необходимо за сключването или изпълнението на договор, сключен в интерес на субекта на данните между администратора и друго физическо или юридическо лице;

г) 

предаването е необходимо поради важни причини от обществен интерес;

д) 

предаването е необходимо за установяването, упражняването или защитата на правни претенции;

е) 

предаването е необходимо, за да бъдат защитени жизненоважните интереси на субекта на данните или на други лица, когато субектът на данните е физически или юридически неспособен да даде своето съгласие;

ж) 

предаването се извършва от регистър, която съгласно правото на Съюза или правото на държавите членки е предназначена да предоставя информация на обществеността и е достъпна за справка от обществеността по принцип или от всяко лице, което може да докаже, че има законен интерес за това, но само доколкото условията за справка, установени в правото на Съюза или правото на държавите членки, са изпълнени в конкретния случай.

Когато предаването не може да се основава на разпоредба на членове 45 или 46, включително разпоредби относно задължителни фирмени правила, и не е приложима нито една от дерогациите в особени случаи, посочени в първата алинея на настоящия параграф, предаването на данни на трета държава или международна организация може да се извършва само ако предаването не е повторяемо, засяга само ограничен брой субекти на данни, необходимо е за целите на неоспоримите законни интереси, преследвани от администратора, над които не стоят интересите или правата и свободите на субекта на данни и администраторът е оценил всички обстоятелства, свързани с предаването на данните, и въз основа на тази оценка е предоставил подходящи гаранции във връзка със защитата на личните данни. Администраторът уведомява надзорния орган за предаването на данни. В допълнение към предоставянето на информацията, посочена в членове 13 и 14, администраторът информира субекта на данни за предаването, както и за преследваните неоспоримите законни интереси.
Член 49 2.
Предаването съгласно параграф 1, първа алинея, буква ж) не трябва да включва всички лични данни или всички категории лични данни, съдържащи се в регистъра. Когато регистърът е предназначен за справка от лица, които имат законен интерес, предаването се извършва единствено по искане на тези лица или ако те са получателите.
Член 49 3.
Параграф 1, първа алинея, букви а), б) и в) и параграф 1, втора алинея не се прилагат за дейности, извършвани от публичните органи при упражняването на техните публични правомощия.
Член 49 4.
Общественият интерес, посочен в параграф 1, първа алинея, буква г) се признава в правото на Съюза или правото на държавата членка, което се прилага спрямо администратора.
Член 49 5.
При липсата на решение относно адекватното ниво на защита, правото на Съюза или правото на държава членка може, по важни причини от обществен интерес, изрично да определи ограничения за предаването на специални категории данни на трета държава или международна организация. Държавите членки съобщават тези разпоредби на Комисията.
Член 49 6.
Администраторът или обработващият лични данни документира оценката, както и подходящите гаранции по параграф 1, втора алинея от настоящия член в регистрите, посочени в член 30.

1.1 Препратки

1.2 Идентифицирани изисквания

1.3 Свързани стандарти

2. Идентифицирани изисквания

Изисквания

3. Свързани стандарти

Стандарти
SCF Ad-Hoc Transfers

Description

Mechanisms exist to secure ad-hoc exchanges of large digital files with internal or external parties.

Possible Solutions & Considerations

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

∙ Data classification program
∙ Secure Baseline Configurations (SBC)
∙ Content / DNS filtering

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

∙ Data classification program
∙ Secure Baseline Configurations (SBC)
∙ Content / DNS filtering

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

∙ Data classification program
∙ Secure Baseline Configurations (SBC)
∙ Content / DNS filtering

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

∙ Data classification program
∙ Secure Baseline Configurations (SBC)
∙ Content / DNS filtering∙ Data governance program

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

∙ Data classification program
∙ Secure Baseline Configurations (SBC)
∙ Content / DNS filtering∙ Data governance program

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

Data Classification & Handling (DCH) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with DCH domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ Data management-related activities are decentralized (e.g., a localized/regionalized function) and uses non-standardized methods to implement secure, resilient and compliant practices.
▪ Restrictions for ad-hoc data transfers are primarily administrative in nature (e.g., policies & standards).

Level 2 Planned Tracked

Data Classification & Handling (DCH) 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 DCH domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with DCH 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 DCH domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Data classification and handling-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Data classification and handling management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ A formalized data classification scheme exists to identify categories of data, based on protection requirements from applicable laws, regulations and/or contractual obligations.
▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to document where sensitive/regulated data is stored, transmitted and/or processed.

Level 3 Well Defined

Data Classification & Handling (DCH) 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 DCH 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 DCH domain capabilities are well-documented and kept current by process owners.
▪ A Governance, Risk & Compliance (GRC) team, or similar function, is appropriately staffed and supported to implement and maintain DCH domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of data classification and handling operations (e.g., GRC 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 DCH 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 secure ad-hoc exchanges of large digital files with internal or external parties.

Level 4 Quantitatively Controlled

Data Classification & Handling (DCH) 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

Data Classification & Handling (DCH) 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.
▪ Based on predictive analysis, process improvements are implemented according to “continuous improvement” practices that affect process changes.
▪ Stakeholders make time-sensitive decisions to support operational efficiency, which may include automated remediation actions via Artificial Intelligence (AI) or Machine Learning (ML) technologies.
SCF External Transfer of Sensitive / Regulated Data

Description

Mechanisms exist to restrict and govern the transfer of sensitive and/or regulated data:
(1) Cross-border; and/or
(2) Interorganizational.

Possible Solutions & Considerations

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

∙ Model contracts
∙ Binding Corporate Rules (BCR)

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

∙ Model contracts
∙ Binding Corporate Rules (BCR)

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

∙ Model contracts
∙ Binding Corporate Rules (BCR)

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

∙ Model contracts
∙ Binding Corporate Rules (BCR)

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

∙ Model contracts
∙ Binding Corporate Rules (BCR)

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

SCR-CMM Level 1 criteria definitions are not available for this control:
▪ A reasonable person would conclude this control requires a structured process.
▪ At this level of maturity, the "ad hoc" nature of performing a capability informally would indicate the intent of the control is not met due to a lack of consistency and formality.

Level 2 Planned Tracked

Data Classification & Handling (DCH) 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 DCH domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with DCH 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 DCH domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Data classification and handling-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Data classification and handling management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ A formalized data classification scheme exists to identify categories of data, based on protection requirements from applicable laws, regulations and/or contractual obligations.

Level 3 Well Defined

Data Classification & Handling (DCH) 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 DCH 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 DCH domain capabilities are well-documented and kept current by process owners.
▪ A Governance, Risk & Compliance (GRC) team, or similar function, is appropriately staffed and supported to implement and maintain DCH domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of data classification and handling operations (e.g., GRC 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 DCH 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 restrict and govern the transfer of sensitive and/or regulated data to third-countries or international organizations.

Level 4 Quantitatively Controlled

Data Classification & Handling (DCH) 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

Data Classification & Handling (DCH) 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.
▪ Based on predictive analysis, process improvements are implemented according to “continuous improvement” practices that affect process changes.
▪ Stakeholders make time-sensitive decisions to support operational efficiency, which may include automated remediation actions via Artificial Intelligence (AI) or Machine Learning (ML) technologies.