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 : DAS-C01
Exam Name : AWS Certified Data Analytics - Specialty (DAS-C01)
Vendor Name : Amazon
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DAS-C01 test Format | DAS-C01 Course Contents | DAS-C01 Course Outline | DAS-C01 test Syllabus | DAS-C01 test Objectives
Exam Detail:
The DAS-C01 AWS Certified Data Analytics - Specialty test is designed to validate the knowledge and skills of individuals working with data analytics on the Amazon Web Services (AWS) platform. Here are the test details for the DAS-C01 exam:
- Number of Questions: The test typically consists of multiple-choice and multiple-response questions. The exact number of questions may vary, but it is typically around 65-75 questions.
- Time Limit: The time allotted to complete the test is 170 minutes (2 hours and 50 minutes).
Course Outline:
The DAS-C01 certification test covers a wide range of Topics related to data analytics on AWS. The course outline typically includes the following domains:
1. Collection, Storage, and Data Management:
- Understanding AWS data collection services, such as AWS Data Pipeline, AWS Glue, and AWS Database Migration Service (DMS).
- Implementing data storage and data management solutions using AWS services like Amazon S3, Amazon Redshift, and Amazon DynamoDB.
- Configuring data access and security controls.
2. Processing:
- Designing and implementing data processing solutions using AWS services like Amazon EMR, AWS Lambda, and AWS Glue.
- Transforming and enriching data using AWS Glue and AWS Lambda functions.
- Implementing data governance and data quality controls.
3. Analysis and Visualization:
- Leveraging AWS services like Amazon Athena, Amazon QuickSight, and Amazon Quicksight to perform data analysis and visualization.
- Designing and optimizing queries and data analysis workflows.
- Creating interactive and insightful dashboards and visualizations.
4. Machine Learning:
- Understanding the principles of machine learning (ML) and its application in data analytics.
- Implementing ML solutions using AWS services like Amazon SageMaker, AWS Glue, and Amazon Rekognition.
- Evaluating and optimizing ML models.
Exam Objectives:
The objectives of the DAS-C01 test are as follows:
- Assessing candidates' knowledge of AWS data analytics services and their capabilities.
- Evaluating candidates' proficiency in designing and implementing data collection, storage, and management solutions.
- Testing candidates' ability to process and transform data using AWS data analytics services.
- Assessing candidates' understanding of data analysis and visualization techniques using AWS services.
- Evaluating candidates' knowledge of machine learning principles and their application in data analytics on AWS.
Exam Syllabus:
The specific test syllabus for the DAS-C01 test covers the following topics:
1. Domain 1: Collection, Storage, and Data Management:
- AWS data collection services.
- Data storage solutions on AWS.
- Data management and security controls.
2. Domain 2: Processing:
- AWS data processing services.
- Data transformation and enrichment using AWS services.
- Data governance and data quality.
3. Domain 3: Analysis and Visualization:
- AWS services for data analysis and visualization.
- Query optimization and performance tuning.
- Dashboard creation and interactive visualizations.
4. Domain 4: Machine Learning:
- Machine learning principles and concepts.
- AWS machine learning services.
- ML model evaluation and optimization.
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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