Skip to main content

Cybersecurity Frameworks

Cyber security frameworks are sets of documents describing guidelines, standards, and best practices designed for cyber security risk management. The frameworks exist to reduce an organization's exposure to weaknesses and vulnerabilities that hackers and other cyber criminals may exploit.

A cybersecurity framework is a set of policies, practices, and procedures implemented to create an effective cybersecurity posture. These frameworks provide organizations with the guidance to protect their assets from cyberthreats by identifying, assessing, and managing risks that could lead to data breaches, system outages, or other disruptions.

  • NIST Cybersecurity Framework
  • ISO 27001 and ISO 27002: International Organization for Standardization.
  • SOC2: Service Organization Control (SOC) Type 2.
  • NERC CIP : North American Electric Reliability Corporation - Critical Infrastructure Protection.
  • HIPAA : Health Insurance Portability and Accountability Act.
  • GDPR: The General Data Protection Regulation.
  • FISMA: The Federal Information Security Management Act.
  • PCI DSS
NIST SF:


PCI-DSS

A council of major payment processors developed the Payment Card Industry Data Security Standard (PCI-DSS) to protect customers’ payment card data. This standard provides a comprehensive set of requirements designed to help organizations secure their systems and prevent unauthorized access to customer information.

The PCI-DSS framework includes 12 requirements organizations must meet to protect customer data. These requirements cover access control, network security, and data storage specific to the payment processing industry. It also includes measures for safeguarding customer payment card data, including encryption and tokenization technologies.

On March 31, 2024, PCI-DSS version 3.2.1 officially retired, and version 4.0 became mandatory, now requiring the use of multi-factor authentication.




Comments

Popular posts from this blog

Microservices design patterns

Microservices design pattern Next :  saga-design-pattern-microservices

Runtime Fabric (RTF)

MuleSoft's Anypoint Runtime Fabric (RTF) has many features that help with deployment and management of Mule applications: Deployment: RTF can deploy applications to any environment, including on-premises, in the cloud, or in a hybrid setup. It can also automatically deploy Mule runtimes into containers. Isolation: RTF can isolate applications by running a separate Mule runtime server for each application. Scaling: RTF can scale applications across multiple replicas. Fail-over: RTF can automatically fail over applications. Monitoring and logging: RTF has built-in monitoring and logging capabilities to help teams troubleshoot issues and gain insights into application performance. Containerization: RTF supports containerization, which allows applications to be packaged with their dependencies and run consistently across different environments. Integration: RTF can integrate with services like SaveMyLeads to automate data flow between applications. Management: RTF can be managed with A...

Integration Design Patterns

Understanding Integration Design Patterns: Integration design patterns serve as reusable templates for solving common integration problems encountered in software development. They encapsulate best practices and proven solutions, empowering developers to architect complex systems with confidence. These patterns abstract away the complexities of integration, promoting modularity, flexibility, and interoperability across components. Most Common Integration Design Patterns: Point-to-Point Integration: Point-to-Point Integration involves establishing direct connections between individual components. While simple to implement, this pattern can lead to tight coupling and scalability issues as the number of connections grows. Visualizing this pattern, imagine a network of interconnected nodes, each communicating directly with specific endpoints. Publish-Subscribe (Pub/Sub) Integration: Pub/Sub Integration decouples producers of data (publishers) from consumers (subscribers) through a central ...