Direct links from the subject.
| Property | Value |
|---|---|
|
The subject is an instance of a class. |
|
|
The subject is an instance of a class. |
An idea or notion; a unit of thought. |
|
A human-readable name for the subject. |
DE.CM-01.2: Anti-virus, -spyware, and other -malware programs shall be installed and updated. |
|
DE.CM-01.2 |
|
|
http://cyfun.data.gift/data/loc_CyFun2025_Booklet_BASIC_E_p42 |
|
|
http://cyfun.data.gift/data/loc_CyFun2025_Booklet_ESSENTIAL_E_p146 |
|
|
http://cyfun.data.gift/data/loc_CyFun2025_Booklet_IMPORTANT_E_p98 |
|
|
Relates a concept to a concept that is more general in meaning. |
|
|
A general note, for any purpose. |
<div><p>The goal of this control is to ensure that the organisation can detect and respond to risky or suspicious behaviour by users on both devices and networks. This helps identify threats such as malware infections, misuse of systems, or attempts to bypass security controls — whether caused by external attackers or insiders. To achieve this goal, the following should be considered:</p><ul><li>Organisations should consider using a combination of modern security tools that work together to provide a full picture of user and system activity:<ul><li>Intrusion Detection and Prevention Systems (IDPS): These tools monitor network traffic and can block or alert on suspicious activity, such as hacking attempts or exploitation of vulnerabilities.</li><li>WebApplication Firewalls (WAFs) and API Gateways:These help protect online applications and services by filtering harmful traffic and preventing unauthorised access.</li></ul></li><li>In addition, a layered approach using advanced detection and response tools can provide real-time visibility and faster response:<ul><li>Endpoint Detection and Response (EDR): Monitors activity on individual devices (like laptops or servers) to detect threats such as malware or unauthorised access.</li><li>Network Detection and Response (NDR): Analyses network traffic to identify unusual patterns, such as lateral movement or hidden attacks.</li><li>Identity Threat Detection and Response (ITDR): Focuses on detecting misuse of user accounts, such as stolen credentials or insider threats.</li><li>User and Entity BehaviourAnalytics (UEBA): Uses machine learning to understand normal behaviour and detect anomalies that may indicate a threat.</li></ul></li><li>These tools are part of a modern, layered security strategy and are often referenced in industry best prac- tices and frameworks such as the Security Operations Centre (SOC) Visibility Triad introduced by Gartner.</li></ul></div> |
|
A general note, for any purpose. |
The goal of this control is to ensure that the organisation can detect and respond to risky or suspicious behaviour by users on both devices and networks. This helps identify threats such as malware infections, misuse of systems, or attempts to bypass security controls — whether caused by external attackers or insiders. To achieve this goal, the following should be considered: - Organisations should consider using a combination of modern security tools that work together to provide a full picture of user and system activity: - Intrusion Detection and Prevention Systems (IDPS): These tools monitor network traffic and can block or alert on suspicious activity, such as hacking attempts or exploitation of vulnerabilities. - WebApplication Firewalls (WAFs) and API Gateways:These help protect online applications and services by filtering harmful traffic and preventing unauthorised access. - In addition, a layered approach using advanced detection and response tools can provide real-time visibility and faster response: - Endpoint Detection and Response (EDR): Monitors activity on individual devices (like laptops or servers) to detect threats such as malware or unauthorised access. - Network Detection and Response (NDR): Analyses network traffic to identify unusual patterns, such as lateral movement or hidden attacks. - Identity Threat Detection and Response (ITDR): Focuses on detecting misuse of user accounts, such as stolen credentials or insider threats. - User and Entity BehaviourAnalytics (UEBA): Uses machine learning to understand normal behaviour and detect anomalies that may indicate a threat. - These tools are part of a modern, layered security strategy and are often referenced in industry best prac- tices and frameworks such as the Security Operations Centre (SOC) Visibility Triad introduced by Gartner. |
|
A general note, for any purpose. |
The goal of this control is to ensure that the organisation can detect and respond to risky or suspicious behaviour by users on both devices and networks. This helps identify threats such as malware infections, misuse of systems, or attempts to bypass security controls — whether caused by external attackers or insiders. To achieve this goal, the following should be considered: • Organisations should consider using a combination of modern security tools that work together to provide a full picture of user and system activity: o Intrusion Detection and Prevention Systems (IDPS): These tools monitor network traffic and can block or alert on suspicious activity, such as hacking attempts or exploitation of vulnerabilities. o WebApplication Firewalls (WAFs) and API Gateways:These help protect online applications and services by filtering harmful traffic and preventing unauthorised access. • In addition, a layered approach using advanced detection and response tools can provide real-time visibility and faster response: o Endpoint Detection and Response (EDR): Monitors activity on individual devices (like laptops or servers) to detect threats such as malware or unauthorised access. o Network Detection and Response (NDR): Analyses network traffic to identify unusual patterns, such as lateral movement or hidden attacks. o Identity Threat Detection and Response (ITDR): Focuses on detecting misuse of user accounts, such as stolen credentials or insider threats. o User and Entity BehaviourAnalytics (UEBA): Uses machine learning to understand normal behaviour and detect anomalies that may indicate a threat. • These tools are part of a modern, layered security strategy and are often referenced in industry best prac- tices and frameworks such as the Security Operations Centre (SOC) Visibility Triad introduced by Gartner. |
|
A general note, for any purpose. |
The goal of this control is to ensure that the organisation can detect and respond to risky or suspicious behaviour by users on both devices and networks. This helps identify threats such as malware infections, misuse of systems, or attempts to bypass security controls — whether caused by external attackers or insiders. To achieve this goal, the following should be considered: - Organisations should consider using a combination of modern security tools that work together to provide a full picture of user and system activity: - Intrusion Detection and Prevention Systems (IDPS): These tools monitor network traffic and can block or alert on suspicious activity, such as hacking attempts or exploitation of vulnerabilities. - WebApplication Firewalls (WAFs) and API Gateways:These help protect online applications and services by filtering harmful traffic and preventing unauthorised access. - In addition, a layered approach using advanced detection and response tools can provide real-time visibility and faster response: - Endpoint Detection and Response (EDR): Monitors activity on individual devices (like laptops or servers) to detect threats such as malware or unauthorised access. - Network Detection and Response (NDR): Analyses network traffic to identify unusual patterns, such as lateral movement or hidden attacks. - Identity Threat Detection and Response (ITDR): Focuses on detecting misuse of user accounts, such as stolen credentials or insider threats. - User and Entity BehaviourAnalytics (UEBA): Uses machine learning to understand normal behaviour and detect anomalies that may indicate a threat. - These tools are part of a modern, layered security strategy and are often referenced in industry best prac- tices and frameworks such as the Security Operations Centre (SOC) Visibility Triad introduced by Gartner. |
|
A notation, also known as classification code, is a string of characters such as "T58.5" or "303.4833" used to uniquely identify a concept within the scope of a given concept scheme. |
DE.CM-01.2 |
|
skos:prefLabel, skos:altLabel and skos:hiddenLabel are pairwise disjoint properties. |
Anti-malware installation and updates |
|
A resource has no more than one value of skos:prefLabel per language tag, and no more than one value of skos:prefLabel without language tag. |
Anti-virus, -spyware, and other -malware programs shall be installed and updated. |
|
Relates a resource (for example a concept) to a concept scheme in which it is included. |
|
|
Relates a resource (for example a concept) to a concept scheme in which it is included. |
|
|
Relates a resource (for example a concept) to a concept scheme in which it is included. |
|
|
Relates a resource (for example a concept) to a concept scheme in which it is included. |
|
|
Relates a resource (for example a concept) to a concept scheme in which it is included. |
|
|
Relates a resource (for example a concept) to a concept scheme in which it is included. |
|
|
1 |
|
|
The number of triples associated with the subject. |
23 |
|
Specifies the dataset the subject is part of. |
Resultaten 1 - 25 of 25
Inverse links to the subject.
| Property | Subject |
|---|---|
|
Relates a concept to a concept that is more specific in meaning. |
Resultaten 1 - 1 of 1