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 : DCPDS
Exam Name : Databricks Certified Professional Data Scientist
Vendor Name : Databricks
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DCPDS test Format | DCPDS Course Contents | DCPDS Course Outline | DCPDS test Syllabus | DCPDS test Objectives

Exam Detail:
The DCPDS (Databricks Certified Professional Data Scientist) test is a certification test that validates the knowledge and skills of individuals in data science using Databricks. Here are the test details for the DCPDS certification:

- Number of Questions: The test typically consists of multiple-choice questions and hands-on exercises. The exact number of questions may vary, but typically, the test includes around 60 to 80 questions.

- Time Limit: The time allocated to complete the test is 2 hours (120 minutes).

Course Outline:
The DCPDS certification course covers various Topics related to data science using Databricks. The course outline typically includes the following topics:

1. Introduction to Databricks:
- Understanding the basics of Databricks and its role in data science.
- Navigating the Databricks workspace and user interface.

2. Data Exploration and Preparation:
- Exploring and understanding data using Databricks.
- Performing data preprocessing tasks such as data cleaning, transformation, and feature engineering.

3. Machine Learning with Databricks:
- Applying machine learning algorithms and techniques using Databricks.
- Building and training machine learning models.
- Evaluating and tuning model performance.

4. Advanced Analytics and Visualization:
- Using Databricks for advanced analytics tasks such as clustering, time series analysis, and text analysis.
- Visualizing data and model results using Databricks' visualization tools.

5. Model Deployment and Monitoring:
- Deploying machine learning models in production using Databricks.
- Monitoring and evaluating model performance and making necessary adjustments.

6. Collaborative Workflows:
- Working collaboratively with other data scientists and stakeholders in Databricks.
- Sharing and presenting insights and results using Databricks' collaboration features.

Exam Objectives:
The objectives of the DCPDS test are as follows:

- Assessing candidates' understanding of Databricks and its role in data science.
- Evaluating candidates' knowledge and proficiency in data exploration and preparation using Databricks.
- Testing candidates' skills in applying machine learning algorithms and techniques using Databricks.
- Assessing candidates' ability to perform advanced analytics tasks and visualize data in Databricks.
- Evaluating candidates' competence in deploying and monitoring machine learning models in Databricks.
- Testing candidates' understanding of collaborative workflows and effective communication in Databricks.

Exam Syllabus:
The specific test syllabus for the DCPDS certification covers the following areas:

1. Databricks Basics: Understanding the Databricks workspace, user interface, and collaborative features.

2. Data Exploration and Preparation: Performing data exploration, cleaning, and transformation using Databricks.

3. Machine Learning with Databricks: Applying machine learning algorithms and techniques in Databricks.

4. Advanced Analytics and Visualization: Performing advanced analytics tasks and visualizing data in Databricks.

5. Model Deployment and Monitoring: Deploying and monitoring machine learning models in Databricks.

6. Collaborative Workflows: Working collaboratively and effectively communicating with stakeholders in Databricks.

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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

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Cyber-Kosten:

Cyber-Drittschäden (Haftpflicht):

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