Was ist das eigentlich? Cyberrisiken verständlich erklärt

Es wird viel über Cyberrisiken gesprochen. Oftmals fehlt aber das grundsätzliche Verständnis, was Cyberrisiken überhaupt sind. Ohne diese zu verstehen, lässt sich aber auch kein Versicherungsschutz gestalten.

Beinahe alle Aktivitäten des täglichen Lebens können heute über das Internet abgewickelt werden. Online-Shopping und Online-Banking sind im Alltag angekommen. Diese Entwicklung trifft längst nicht nur auf Privatleute, sondern auch auf Firmen zu. Das Schlagwort Industrie 4.0 verheißt bereits eine zunehmende Vernetzung diverser geschäftlicher Vorgänge über das Internet.

Anbieter von Cyberversicherungen für kleinere und mittelständische Unternehmen (KMU) haben Versicherungen die Erfahrung gemacht, dass trotz dieser eindeutigen Entwicklung Cyberrisiken immer noch unterschätzt werden, da sie als etwas Abstraktes wahrgenommen werden. Für KMU kann dies ein gefährlicher Trugschluss sein, da gerade hier Cyberattacken existenzbedrohende Ausmaße annehmen können. So wird noch häufig gefragt, was Cyberrisiken eigentlich sind. Diese Frage ist mehr als verständlich, denn ohne (Cyber-)Risiken bestünde auch kein Bedarf für eine (Cyber-)Versicherung.

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Exam Name : Google Cloud Certified - Professional Cloud DevOps Engineer
Vendor Name : Google
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Professional-Cloud-DevOps-Engineer exam Format | Professional-Cloud-DevOps-Engineer Course Contents | Professional-Cloud-DevOps-Engineer Course Outline | Professional-Cloud-DevOps-Engineer exam Syllabus | Professional-Cloud-DevOps-Engineer exam Objectives


Exam Specification: Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer)

Exam Name: Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer)
Exam Code: Professional-Cloud-DevOps-Engineer
Exam Duration: 2 hours
Passing Score: Not specified
Exam Format: Multiple-choice

Course Outline:

1. Introduction to DevOps on Google Cloud Platform
- Understanding DevOps principles and practices
- Overview of Google Cloud Platform (GCP) and its services
- Role of a DevOps Engineer in managing and deploying applications on GCP

2. Continuous Integration and Delivery (CI/CD)
- Setting up CI/CD pipelines using Google Cloud Build
- Configuration and management of source code repositories
- Automating builds, tests, and deployments using CI/CD tools on GCP

3. Infrastructure as Code (IaC)
- Introduction to infrastructure as code concepts
- Managing infrastructure using Google Cloud Deployment Manager
- Using Terraform and other tools for infrastructure provisioning on GCP

4. Monitoring and Logging
- Configuring monitoring and alerting using Google Cloud Monitoring
- Leveraging Google Cloud Logging for centralized log management
- Analyzing and troubleshooting application and infrastructure issues using GCP tools

5. Scalability and Performance Optimization
- Designing and implementing scalable and highly available architectures on GCP
- Optimizing performance and resource utilization for applications on GCP
- Load balancing, auto-scaling, and capacity planning strategies on GCP

6. Security and Compliance
- Implementing security controls and best practices on GCP
- Managing access and permissions using Google Cloud Identity and Access Management (IAM)
- Ensuring compliance with industry standards and regulations on GCP

Exam Objectives:

1. Understand DevOps principles and practices and their application on Google Cloud Platform.
2. Configure and manage continuous integration and delivery pipelines using Google Cloud Build.
3. Implement infrastructure as code using tools like Google Cloud Deployment Manager and Terraform.
4. Set up monitoring and logging solutions to ensure the availability and performance of applications on GCP.
5. Design and optimize scalable and highly available architectures on Google Cloud Platform.
6. Implement security controls and ensure compliance with industry standards on GCP.

Exam Syllabus:

Section 1: Introduction to DevOps on Google Cloud Platform (15%)
- DevOps principles and practices
- Overview of Google Cloud Platform and its services
- Role of a DevOps Engineer on GCP

Section 2: Continuous Integration and Delivery (CI/CD) (20%)
- Configuring CI/CD pipelines with Google Cloud Build
- Source code repository management
- Automation of builds, tests, and deployments on GCP

Section 3: Infrastructure as Code (IaC) (15%)
- Infrastructure as code concepts
- Managing infrastructure with Google Cloud Deployment Manager
- Using Terraform and other tools for infrastructure provisioning on GCP

Section 4: Monitoring and Logging (15%)
- Configuration of monitoring and alerting using Google Cloud Monitoring
- Centralized log management with Google Cloud Logging
- Application and infrastructure troubleshooting using GCP tools

Section 5: Scalability and Performance Optimization (20%)
- Designing scalable and highly available architectures on GCP
- Performance optimization techniques for GCP applications
- Load balancing, auto-scaling, and capacity planning strategies on GCP

Section 6: Security and Compliance (15%)
- Implementing security controls and best practices on GCP
- Managing access and permissions with Google Cloud IAM
- Ensuring compliance with industry standards on GCP



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GCP vs AWS Comparison: Unveiling the Ultimate Cloud Winner

In the dynamic world of cloud computing, two giants have emerged as the frontrunners, captivating the attention of businesses and tech enthusiasts alike. Google Cloud Platform (GCP) and Amazon Web Services (AWS) are two of the most prominent players in the cloud services domain, each offering a plethora of tools, services, and features. The battle between GCP and AWS has fueled countless debates over which platform reigns supreme. In this blog, they delve into the GCP vs AWS comparison, aiming to unravel the strengths, weaknesses, and key differentiators of these two cloud titans.

Feature-Rich Offerings

Both GCP and AWS offer an extensive array of cloud services, from computing and storage to databases, machine learning, and more. AWS, being the pioneer in cloud computing, boasts a vast collection of services that cater to virtually any business need. On the other hand, GCP brings the innovation prowess of Google to the table, offering advanced machine learning tools and data analytics services.

GCP's advantage lies in its data-centric approach, well-suited for organizations seeking robust analytics capabilities. Its BigQuery service, for instance, enables lightning-fast querying and analysis of massive datasets. This makes GCP a natural choice for data-driven enterprises looking to derive insights from their information treasure troves.

AWS, however, maintains its lead in sheer service variety, with a vast selection of services to cater to diverse business needs. From the EC2 compute instances that power applications to S3 for scalable storage, AWS provides a comprehensive suite of services that can be customized to fit any project's requirements.

Scalability and Flexibility

Scalability is a cornerstone of cloud computing, allowing businesses to seamlessly grow or shrink their resources based on demand. Both GCP and AWS offer auto-scaling capabilities, allowing applications to dynamically adjust to varying workloads.

GCP introduces Kubernetes, an open-source container orchestration platform that simplifies the management of containers at scale. This service aligns well with Google's expertise in managing massive workloads efficiently, providing users with a robust tool for deploying and managing containerized applications.

AWS, meanwhile, has its Elastic Kubernetes Service (EKS) that provides a managed Kubernetes environment. Moreover, AWS's Lambda takes a serverless computing approach, enabling developers to execute code without the need to set up or handle servers. This serverless approach has simplified application deployment and scaling for many businesses.

Pricing Models and Cost Management

For businesses, understanding and managing costs are crucial in the cloud environment. GCP and AWS each have their pricing models and cost management tools to help users optimize their spending.

GCP's pricing is often appreciated for its transparency and simplicity, with features like "Sustained Use Discounts" and "Committed Use Contracts" offering flexibility and cost savings for sustained workloads. Google's "Per-Second Billing" approach is another highlight, allowing users to pay for what they consume without unnecessary charges.

AWS, while having a more complex pricing structure, provides a wide range of pricing options based on usage patterns. Reserved Instances and Savings Plans offer substantial cost savings for businesses with predictable workloads, and the "Pay-as-You-Go" model remains a flexible choice for varying demands.

Innovation and Machine Learning

When it comes to innovation, GCP leverages Google's expertise in AI and machine learning. Google's Tensor Processing Units (TPUs) provide powerful acceleration for machine learning workloads, making GCP an attractive choice for organizations involved in AI-driven projects.

AWS, too, doesn't lag behind in the innovation race. With Amazon SageMaker, AWS's integrated machine learning service, businesses can build, train, and deploy machine learning models at scale. AWS's large customer base also contributes to the development of cutting-edge services and features that cater to diverse needs.

Conclusion

In the GCP vs AWS battle, it's evident that both platforms bring their unique strengths to the table. GCP shines in data analytics and machine learning, with Google's innovation at its core. AWS, on the other hand, boasts a vast array of services and a mature ecosystem, making it a versatile choice for a wide range of business needs.

In the end, declaring an ultimate winner between GCP and AWS depends on the specific requirements of your organization. While GCP might be the right fit for data-intensive projects and AI-driven innovations, AWS's extensive service offerings and scalability might be more appealing to businesses looking for versatility and reliability.

Whichever platform you choose, the competition between GCP and AWS continues to drive innovation, pushing the boundaries of what's possible in the world of cloud computing. As technology evolves, so will these cloud giants, ensuring that businesses have the tools they need to succeed in a rapidly changing digital landscape.


How Amazon is racing to catch Microsoft and Google in generative A.I. with custom AWS chips

No result found, try new keyword!CNBC got an exclusive look inside Amazon's chip lab, where AWS designs custom silicon in a race to catch Microsoft and Google in the generative A.I. race ...
 


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Warum sind Cyberrisiken so schwer greifbar?

Als mehr oder weniger neuartiges Phänomen stellen Cyberrisiken Unternehmen und Versicherer vor besondere Herausforderungen. Nicht nur die neuen Schadenszenarien sind abstrakter oder noch nicht bekannt. Häufig sind immaterielle Werte durch Cyberrisiken in Gefahr. Diese wertvollen Vermögensgegenstände sind schwer bewertbar.

Obwohl die Gefahr durchaus wahrgenommen wird, unterschätzen viele Firmen ihr eigenes Risiko. Dies liegt unter anderem auch an den Veröffentlichungen zu Cyberrisiken. In der Presse finden sich unzählige Berichte von Cyberattacken auf namhafte und große Unternehmen. Den Weg in die Presse finden eben nur die spektakulären Fälle. Die dort genannten Schadenszenarien werden dann für das eigene Unternehmen als unrealistisch eingestuft. Die für die KMU nicht minder gefährlichen Cyber­attacken werden nur selten publiziert.

Aufgrund der fehlenden öffentlichen Meldungen von Sicherheitsvorfällen an Sicherheitsbehörden und wegen der fehlenden Presseberichte fällt es schwer, Fakten und Zahlen zur Risikolage zu erheben. Aber ohne diese Grundlage fällt es schwer, in entsprechende Sicherheitsmaßnahmen zu investieren.

Erklärungsleitfaden anhand eines Ursache-Wirkungs-Modells

Häufig nähert man sich dem Thema Cyberrisiko anlass- oder eventbezogen, also wenn sich neue Schaden­szenarien wie die weltweite WannaCry-Attacke entwickeln. Häufig wird auch akteursgebunden beleuchtet, wer Angreifer oder Opfer sein kann. Dadurch begrenzt man sich bei dem Thema häufig zu sehr nur auf die Cyberkriminalität. Um dem Thema Cyberrisiko jedoch gerecht zu werden, müssen auch weitere Ursachen hinzugezogen werden.

Mit einer Kategorisierung kann das Thema ganzheitlich und nachvollziehbar strukturiert werden. Ebenso hilft eine solche Kategorisierung dabei, eine Abgrenzung vorzunehmen, für welche Gefahren Versicherungsschutz über eine etwaige Cyberversicherung besteht und für welche nicht.

Die Ursachen sind dabei die Risiken, während finanzielle bzw. nicht finanzielle Verluste die Wirkungen sind. Cyberrisiken werden demnach in zwei Hauptursachen eingeteilt. Auf der einen Seite sind die nicht kriminellen Ursachen und auf der anderen Seite die kriminellen Ursachen zu nennen. Beide Ursachen können dabei in drei Untergruppen unterteilt werden.

Nicht kriminelle Ursachen

Höhere Gewalt

Häufig hat man bei dem Thema Cyberrisiko nur die kriminellen Ursachen vor Augen. Aber auch höhere Gewalt kann zu einem empfindlichen Datenverlust führen oder zumindest die Verfügbarkeit von Daten einschränken, indem Rechenzentren durch Naturkatastrophen wie beispielsweise Überschwemmungen oder Erdbeben zerstört werden. Ebenso sind Stromausfälle denkbar.

Menschliches Versagen/Fehlverhalten

Als Cyberrisiken sind auch unbeabsichtigtes und menschliches Fehlverhalten denkbar. Hierunter könnte das versehentliche Veröffentlichen von sensiblen Informationen fallen. Möglich sind eine falsche Adressierung, Wahl einer falschen Faxnummer oder das Hochladen sensibler Daten auf einen öffentlichen Bereich der Homepage.

Technisches Versagen

Auch Hardwaredefekte können zu einem herben Datenverlust führen. Neben einem Überhitzen von Rechnern sind Kurzschlüsse in Systemtechnik oder sogenannte Headcrashes von Festplatten denkbare Szenarien.

Kriminelle Ursachen

Hackerangriffe

Hackerangriffe oder Cyberattacken sind in der Regel die Szenarien, die die Presse dominieren. Häufig wird von spektakulären Datendiebstählen auf große Firmen oder von weltweiten Angriffen mit sogenannten Kryptotrojanern berichtet. Opfer kann am Ende aber jeder werden. Ziele, Methoden und auch das Interesse sind vielfältig. Neben dem finanziellen Interesse können Hackerangriffe auch zur Spionage oder Sabotage eingesetzt werden. Mögliche Hackermethoden sind unter anderem: Social Engineering, Trojaner, DoS-Attacken oder Viren.

Physischer Angriff

Die Zielsetzung eines physischen Angriffs ist ähnlich dem eines Hacker­angriffs. Dabei wird nicht auf die Tools eines Hackerangriffs zurückgegriffen, sondern durch das physische Eindringen in Unternehmensgebäude das Ziel erreicht. Häufig sind es Mitarbeiter, die vertrauliche Informationen stehlen, da sie bereits den notwendigen Zugang zu den Daten besitzen.

Erpressung

Obwohl die Erpressung aufgrund der eingesetzten Methoden auch als Hacker­angriff gewertet werden könnte, ergibt eine Differenzierung Sinn. Erpressungsfälle durch Kryptotrojaner sind eines der häufigsten Schadenszenarien für kleinere und mittelständische Unternehmen. Außerdem sind auch Erpressungsfälle denkbar, bei denen sensible Daten gestohlen wurden und ein Lösegeld gefordert wird, damit sie nicht veröffentlicht oder weiterverkauft werden.

Ihre Cyberversicherung sollte zumindet folgende Schäden abdecken:

Cyber-Kosten:

  • Soforthilfe und Forensik-Kosten (Kosten der Ursachenermittlung, Benachrichtigungskosten und Callcenter-Leistung)
  • Krisenkommunikation / PR-Maßnahmen
  • Systemverbesserungen nach einer Cyber-Attacke
  • Aufwendungen vor Eintritt des Versicherungsfalls

Cyber-Drittschäden (Haftpflicht):

  • Befriedigung oder Abwehr von Ansprüchen Dritter
  • Rechtswidrige elektronische Kommunikation
  • Ansprüche der E-Payment-Serviceprovider
  • Vertragsstrafe wegen der Verletzung von Geheimhaltungspflichten und Datenschutzvereinbarungen
  • Vertragliche Schadenersatzansprüche
  • Vertragliche Haftpflicht bei Datenverarbeitung durch Dritte
  • Rechtsverteidigungskosten

Cyber-Eigenschäden:

  • Betriebsunterbrechung
  • Betriebsunterbrechung durch Ausfall von Dienstleister (optional)
  • Mehrkosten
  • Wiederherstellung von Daten (auch Entfernen der Schadsoftware)
  • Cyber-Diebstahl: elektronischer Zahlungsverkehr, fehlerhafter Versand von Waren, Telefon-Mehrkosten/erhöhte Nutzungsentgelte
  • Cyber-Erpressung
  • Entschädigung mit Strafcharakter/Bußgeld
  • Ersatz-IT-Hardware
  • Cyber-Betrug