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 : AI-900
Exam Name : Microsoft Azure AI Fundamentals
Vendor Name : Microsoft
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AI-900 exam Format | AI-900 Course Contents | AI-900 Course Outline | AI-900 exam Syllabus | AI-900 exam Objectives

EXAM NUMBER : AI-900
EXAM NAME : Microsoft Azure AI Fundamentals
Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.

Candidates for the Azure AI Fundamentals certification should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.

This certification is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

This certification is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required;
however, some general programming knowledge or experience would be beneficial.

Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but its not a prerequisite for any of them.

Describe AI workloads and considerations

Describe fundamental principles of machine learning on Azure

Describe features of computer vision workloads on Azure

Describe features of Natural Language Processing (NLP) workloads on Azure

Describe features of conversational AI workloads on Azure

Module 1: Introduction to AI

In this module, you'll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You'll then explore considerations and principles for responsible AI development.

Artificial Intelligence in Azure

Responsible AI

After completing this module you will be able to:

Describe Artificial Intelligence workloads and considerations

Module 2: Machine Learning

Machine learning is the foundation for modern AI solutions. In this module, you'll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

Introduction to Machine Learning

Azure Machine Learning

After completing this module you will be able to:

Describe fundamental principles of machine learning on Azure

Module 3: Computer Vision

Computer vision is a the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you'll explore multiple computer vision techniques and services.

Computer Vision Concepts

Computer Vision in Azure

After completing this module you will be able to:

Describe features of computer vision workloads on Azure

Module 4: Natural Language Processing

This module describes scenarios for AI solutions that can process written and spoken language. You'll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands.

After completing this module you will be able to:

Describe features of Natural Language Processing (NLP) workloads on Azure

Module 5: Conversational AI

Conversational AI enables users to engage in a dialog with an AI agent, or bot, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions.

Conversational AI Concepts

Conversational AI in Azure

After completing this module you will be able to:

Describe features of conversational AI workloads on Azure

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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):

Cyber-Eigenschäden:

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