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 Number : SAA-C03
Exam Name : AWS Certified Solutions Architect - Associate
Vendor Name : Amazon
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SAA-C03 exam Format | SAA-C03 Course Contents | SAA-C03 Course Outline | SAA-C03 exam Syllabus | SAA-C03 exam Objectives
Title: AWS Certified Solutions Architect - Associate (SAA-C03)
Test Detail:
The AWS Certified Solutions Architect - Associate (SAA-C03) exam validates the knowledge and skills required to design and deploy scalable, highly available, and fault-tolerant systems on the Amazon Web Services (AWS) platform. This certification is designed for individuals who work as solutions architects and are responsible for designing and implementing AWS-based applications.
Course Outline:
The AWS Certified Solutions Architect - Associate course provides participants with comprehensive knowledge and hands-on experience in designing and deploying applications on AWS. The following is a general outline of the key areas covered in the certification program:
- Design secure access to AWS resources
- Access controls and management across multiple accounts
- AWS federated access and identity services
- AWS Identity and Access Management [IAM]
- AWS IAM Identity Center
- AWS global infrastructure
- Availability Zones
- AWS Regions
- AWS security best practices
- principle of least privilege
- The AWS shared responsibility model
- Applying AWS security best practices to IAM users and root users
- multi-factor authentication [MFA]
- Designing a flexible authorization model
- IAM users
- groups
- roles
- policies
- Designing a role-based access control strategy
- AWS Security Token Service [AWS STS]
- role switching
- cross-account access
- Designing a security strategy for multiple AWS accounts
- AWS Control Tower
- service control policies [SCPs]
- Determining the appropriate use of resource policies for AWS services
- Determining when to federate a directory service with IAM roles
- Design secure workloads and applications.
- Application configuration and credentials security
- AWS service endpoints
- Control ports, protocols, and network traffic on AWS
- Secure application access
- Security services with appropriate use cases
- Amazon Cognito
- Amazon GuardDuty
- Amazon Macie
- Threat vectors external to AWS
- DDoS
- SQL injection
- Designing VPC architectures with security components
- security groups
- route tables
- network ACLs
- NAT gateways
- Determining network segmentation strategies
- using public subnets
- private subnets
- Integrating AWS services to secure applications
-AWS Shield
- AWS WAF
- IAM Identity Center
- AWS Secrets Manager
- Securing external network connections to and from the AWS Cloud
- VPN
- AWS Direct Connect
- Determine appropriate data security controls
- Data access and governance
- Data recovery
- Data retention and classification
- Encryption and appropriate key management
- Aligning AWS technologies to meet compliance requirements
- Encrypting data at rest
- AWS Key Management Service [AWS KMS]
- Encrypting data in transit
- AWS Certificate Manager [ACM] using TLS
- Implementing access policies for encryption keys
- Implementing data backups and replications
- Implementing policies for data access, lifecycle, and protection
- Rotating encryption keys and renewing certificates
- Design scalable and loosely coupled architectures
- API creation and management
- Amazon API Gateway
- REST API
- AWS managed services with appropriate use cases
- AWS Transfer Family
- Amazon Simple Queue Service [Amazon SQS]
- Secrets Manager
- Caching strategies
- Design principles for microservices
- stateless workloads compared with stateful workloads
- Event-driven architectures
- Horizontal scaling and vertical scaling
- How to appropriately use edge accelerators
- content delivery network [CDN]
- How to migrate applications into containers
- Load balancing concepts
- Application Load Balancer
- Multi-tier architectures
- Queuing and messaging concepts
- publish/subscribe
- Serverless technologies and patterns
- AWS Fargate
- AWS Lambda
- Storage types with associated characteristics
- object
- file
- block
- The orchestration of containers
- Amazon Elastic Container Service [Amazon ECS]
- Amazon Elastic Kubernetes Service [Amazon EKS])
- When to use read replicas
- Workflow orchestration
- AWS Step Functions
- Designing event-driven
- microservice and multi-tier architectures based on requirements
- Determining scaling strategies for components used in an architecture design
- Determining the AWS services required to achieve loose coupling based on requirements
- Determining when to use containers
- Determining when to use serverless technologies and patterns
- Recommending appropriate compute, storage, networking, and database technologies based on requirements
- Using purpose-built AWS services for workloads
- Design highly available and/or fault-tolerant architectures
- AWS global infrastructure
- Availability Zones
- AWS Regions
- Amazon Route 53
- AWS managed services with appropriate use cases
- Amazon Comprehend
- Amazon Polly
- Basic networking concepts
- route tables
- Disaster recovery (DR) strategies
- backup and restore
- pilot light
- warm standby
- active-active failover
- recovery point objective [RPO]
- recovery time objective [RTO])
- Distributed design patterns
- Failover strategies
- Immutable infrastructure
- Load balancing concepts
- Application Load Balancer
- Proxy concepts
- Amazon RDS Proxy
- Service quotas and throttling
- how to configure the service quotas for a workload in a standby environment
- Storage options and characteristics
- durability
- replication
- Workload visibility
- AWS X-Ray
- Determining automation strategies to ensure infrastructure integrity
- Determining the AWS services required to provide a highly available and/or fault-tolerant architecture across AWS Regions or Availability Zones
- Identifying metrics based on business requirements to deliver a highly available solution
- Implementing designs to mitigate single points of failure
- Implementing strategies to ensure the durability and availability of data
- backups
- Selecting an appropriate DR strategy to meet business requirements
- Using AWS services that Excellerate the reliability of legacy applications and applications not built for the cloud
- when application changes are not possible
- Using purpose-built AWS services for workloads
- Determine high-performing and/or scalable storage solutions
- Hybrid storage solutions to meet business requirements
- Storage services with appropriate use cases
- Amazon S3
- Amazon Elastic File System [Amazon EFS]
- Amazon Elastic Block Store [Amazon EBS]
- Storage types with associated characteristics
- object
- file
- block
- Determining storage services and configurations that meet performance demands
- Determining storage services that can scale to accommodate future needs
- Design high-performing and elastic compute solutions
- AWS compute services with appropriate use cases
- AWS Batch
- Amazon EMR
- Fargate
- Distributed computing concepts supported by AWS global infrastructure and edge services
- Queuing and messaging concepts
- publish/subscribe
- Scalability capabilities with appropriate use cases
- Amazon EC2 Auto Scaling
- AWS Auto Scaling
- Serverless technologies and patterns
- Lambda
- Fargate
- The orchestration of containers
- Amazon ECS
- Amazon EKS
- Decoupling workloads so that components can scale independently
- Identifying metrics and conditions to perform scaling actions
- Selecting the appropriate compute options and features (for example, EC2 instance types) to meet business requirements
- Selecting the appropriate resource type and size (for example, the amount of Lambda memory) to meet business requirements
- Determine high-performing database solutions
- AWS global infrastructure
- Availability Zones
- AWS Regions
- Caching strategies and services
- Amazon ElastiCache
- Data access patterns
- read-intensive compared with write-intensive
- Database capacity planning
- capacity units
- instance types
- Provisioned IOPS
- Database connections and proxies
- Database engines with appropriate use cases
- heterogeneous migrations
- homogeneous migrations
- Database replication
- read replicas
- Database types and services
- serverless
- relational compared with non-relational
- in-memory
- Configuring read replicas to meet business requirements
- Designing database architectures
- Determining an appropriate database engine
- MySQL compared with PostgreSQL
- Determining an appropriate database type
- Amazon Aurora
- Amazon DynamoDB
- Integrating caching to meet business requirements
- Determine high-performing and/or scalable network architectures
- Edge networking services with appropriate use cases
- Amazon CloudFront
- AWS Global Accelerator
- How to design network architecture
- subnet tiers
- routing, IP addressing
- Load balancing concepts
- Application Load Balancer
- Network connection options
- AWS VPN
- Direct Connect
- AWS PrivateLink
- Creating a network topology for various architectures
- global
- hybrid
- multi-tier
- Determining network configurations that can scale to accommodate future needs
- Determining the appropriate placement of resources to meet business requirements
- Selecting the appropriate load balancing strategy
- High-performing data ingestion and transformation solutions
- Data analytics and visualization services with appropriate use cases
- Amazon Athena
- AWS Lake Formation
- Amazon QuickSight
- Data ingestion patterns
- frequency
- Data transfer services with appropriate use cases
- AWS DataSync
- AWS Storage Gateway
- Data transformation services with appropriate use cases
- AWS Glue
- Secure access to ingestion access points
- Sizes and speeds needed to meet business requirements
- Streaming data services with appropriate use cases
- Amazon Kinesis
- Building and securing data lakes
- Designing data streaming architectures
- Designing data transfer solutions
- Implementing visualization strategies
- Selecting appropriate compute options for data processing
- Amazon EMR
- Selecting appropriate configurations for ingestion
- Transforming data between formats
.csv to .parquet
- Design cost-optimized storage solutions
- Access options
- an S3 bucket with Requester Pays object storage
- AWS cost management service features
- cost allocation tags
- multi-account billing
- AWS cost management tools with appropriate use cases
- AWS Cost Explorer
- AWS Budgets
- AWS Cost
- Usage Report
- AWS storage services with appropriate use cases
- Amazon FSx
- Amazon EFS
- Amazon S3
- Amazon EBS
- Backup strategies
- Block storage options
- hard disk drive [HDD] volume types
- solid state drive [SSD] volume types
- Data lifecycles
- Hybrid storage options
- DataSync
- Transfer Family
- Storage Gateway
- Storage access patterns
- Storage tiering
- cold tiering for object storage
- Storage types with associated characteristics
- object
- file
- block
- Designing appropriate storage strategies
- batch uploads to Amazon S3 compared with individual uploads
- Determining the correct storage size for a workload
- Determining the lowest cost method of transferring data for a workload to AWS storage
- Determining when storage auto scaling is required
- Managing S3 object lifecycles
- Selecting the appropriate backup and/or archival solution
- Selecting the appropriate service for data migration to storage services
- Selecting the appropriate storage tier
- Selecting the correct data lifecycle for storage
- Selecting the most cost-effective storage service for a workload
- Design cost-optimized compute solutions
- AWS cost management service features
- cost allocation tags
- multi-account billing
- AWS cost management tools with appropriate use cases
- Cost Explorer
- AWS Budgets
- AWS Cost
- Usage Report
- AWS global infrastructure
- Availability Zones
- AWS Regions
- AWS purchasing options
- Spot Instances
- Reserved Instances
- Savings Plans
- Distributed compute strategies
- edge processing
- Hybrid compute options
- AWS Outposts
- AWS Snowball Edge
- Instance types, families, and sizes
- memory optimized
- compute optimized
- virtualization
- Optimization of compute utilization
- containers
- serverless computing
- microservices
- Scaling strategies
- auto scaling
- hibernation
- Determining an appropriate load balancing strategy
- Application Load Balancer [Layer 7] compared with Network Load Balancer [Layer 4] compared with Gateway Load Balancer
- Determining appropriate scaling methods and strategies for elastic workloads
- horizontal compared with vertical
- EC2 hibernation
- Determining cost-effective AWS compute services with appropriate use cases
- Lambda
- Amazon EC2
- Fargate
- Determining the required availability for different classes of workloads
- production workloads
- non-production workloads
- Selecting the appropriate instance family for a workload
- Selecting the appropriate instance size for a workload
- Design cost-optimized database solutions
- AWS cost management service features
- cost allocation tags
- multi-account billing
- AWS cost management tools with appropriate use cases
- Cost Explorer
- AWS Budgets
- AWS Cost and Usage Report
- Caching strategies
- Data retention policies
- Database capacity planning
- capacity units
- Database connections and proxies
- Database engines with appropriate use cases
- heterogeneous migrations
- homogeneous migrations
- Database replication
- read replicas
- Database types and services
- relational compared with non-relational
- Aurora
- DynamoDB
- Designing appropriate backup and retention policies
- snapshot frequency
- Determining an appropriate database engine
- MySQL compared with PostgreSQL
- Determining cost-effective AWS database services with appropriate use cases
- DynamoDB compared with Amazon RDS
- serverless
- Determining cost-effective AWS database types
- time series format
- columnar format
- Migrating database schemas and data to different locations and/or different database engines
- Design cost-optimized database solutions
- AWS cost management service features
- cost allocation tags
- multi-account billing
- AWS cost management tools with appropriate use cases
- Cost Explorer
- AWS Budgets
- AWS Cost and Usage Report
- Load balancing concepts
- Application Load Balancer
- NAT gateways
- NAT instance costs compared with NAT gateway costs
- Network connectivity
- private lines
- dedicated lines
- VPNs
- Network routing, topology, and peering
- AWS Transit Gateway
- VPC peering
- Network services with appropriate use cases
- DNS
- Configuring appropriate NAT gateway types for a network
- a single shared NAT gateway compared with NAT gateways for each Availability Zone
- Configuring appropriate network connections
- Direct Connect compared with VPN compared with internet
- Configuring appropriate network routes to minimize network transfer costs
- Region to Region
- Availability Zone to Availability Zone
- private to public
- Global Accelerator
- VPC endpoints
- Determining strategic needs for content delivery networks (CDNs) and edge caching
- Reviewing existing workloads for network optimizations
- Selecting an appropriate throttling strategy
- Selecting the appropriate bandwidth allocation for a network device
- a single VPN compared with multiple VPNs
- Direct Connect speed
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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