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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Microsoft AZ-304 : Microsoft Azure Architect Design exam Dumps

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Exam Number : AZ-304
Exam Name : Microsoft Azure Architect Design
Vendor Name : Microsoft
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AZ-304 exam Format | AZ-304 Course Contents | AZ-304 Course Outline | AZ-304 exam Syllabus | AZ-304 exam Objectives

Test Detail:
The Microsoft AZ-304 exam, also known as Microsoft Azure Architect Design, is a certification exam designed to validate the skills and knowledge of professionals in designing and implementing solutions on the Microsoft Azure platform. The exam assesses the candidate's understanding of Azure architecture, design principles, and best practices. This description provides an overview of the AZ-304 exam.

Course Outline:
The course for the AZ-304 exam covers a wide range of subjects related to Azure architecture and design. The course outline may include the following:

1. Designing for Identity and Security:
- Azure Active Directory (AAD) design and configuration
- Authentication and authorization methods in Azure
- Secure access to Azure resources
- Data protection and encryption in Azure

2. Designing a Data Platform Solution:
- Designing Azure data storage solutions
- Database architecture and design principles
- Data integration and migration strategies
- Implementing data security and privacy

3. Designing for Deployment, Migration, and Integration:
- Designing Azure infrastructure solutions
- Planning for Azure resource deployment
- Azure networking and connectivity design
- Application migration strategies to Azure

4. Designing an Infrastructure Strategy:
- Azure virtual machines and virtual networks design
- High availability and disaster recovery planning
- Azure automation and management solutions
- Monitoring and optimization of Azure resources

Exam Objectives:
The AZ-304 exam objectives cover the following areas:

1. Designing Identity and Security (20-25%)
2. Designing a Data Platform Solution (15-20%)
3. Designing for Deployment, Migration, and Integration (20-25%)
4. Designing an Infrastructure Strategy (15-20%)
5. Designing a Business Continuity Strategy (15-20%)
6. Designing for Cost Optimization (10-15%)

Exam Syllabus:
The AZ-304 exam syllabus includes specific subjects within each of the exam objectives mentioned above. It may cover areas such as:

- Azure Active Directory design and configuration
- Security and access control for Azure resources
- Designing Azure storage solutions (blob storage, file storage, etc.)
- Database design principles and options in Azure
- Hybrid cloud scenarios and connectivity design
- Application deployment and migration strategies to Azure
- Designing highly available and scalable Azure infrastructure
- Disaster recovery and business continuity planning in Azure
- Azure cost management and optimization techniques

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Microsoft cheat sheets: Dive into Windows and Office apps

No result found, try new keyword!Computerworld’s cheat sheets are easy-to-use guides to help you navigate Microsoft’s core productivity apps. Here’s a one-stop resource where you can find in-depth stories on several ...

Microsoft Excel receives Python integration for data analysis and visualization

Microsoft Excel receives Python integration

In a groundbreaking move, Microsoft has unveiled its latest feature for Excel – Python integration. This innovative development brings together the world of Excel and Python analytics, creating a powerful tool for data analysis and visualization. The integration of Python in Excel allows users to utilize potent Python libraries directly within their Excel workbooks. This opens up a world of possibilities, from creating captivating visualizations to building advanced machine learning models.

The integration of Python in Excel is woven directly into the fabric of the software, thanks to the new ‘py’ function. This allows users to use Python seamlessly within the grid, eliminating the need for any additional installations. In a strategic partnership with Anaconda, Microsoft is set to bring a secure and trusted Python distribution for analytics into Excel. This version will include popular Python libraries such as Pandas and Matplotlib, further enhancing the capabilities of Excel.

Excel receives Python support

Other articles you may find of interest on Python and coding :

Python in Excel empowers users to clean and manipulate their data, train machine learning models, create compelling plots, and much more. All of this can be done within the familiar, secure environment of Excel, using Excel’s built-in connectors and Power Query. This makes it easier than ever to bring external data into Python in Excel workflows.

Security and privacy are at the heart of Python in Excel’s design. The Python code runs on the Microsoft cloud as a compliant Microsoft 365 connected service, ensuring the utmost safety and privacy for users. Moreover, Python in Excel is compatible with all the beloved analytics features of Excel, such as formulas, charts, pivot tables, conditional formatting, and more.

The integration of Python in Excel combines the flexibility of Excel with the power of Python, enabling users to make data-informed decisions and tell more compelling stories. With Python in Excel, the future of data analysis and visualization looks brighter than ever.

Pandas Python features

A fast and efficient DataFrame object for data manipulation with integrated indexing;

Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format;

Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form;

Flexible reshaping and pivoting of data sets;

Intelligent label-based slicing, fancy indexing, and subsetting of large data sets;

Columns can be inserted and deleted from data structures for size mutability;

Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets;

High performance merging and joining of data sets;

Hierarchical axis indexing provides an intuitive way of working with high-dimensional data in a lower-dimensional data structure;

Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data;

Highly optimized for performance, with critical code paths written in Cython or C.

Python with pandas is in use in a wide variety of academic and commercial domains, including Finance, Neuroscience, Economics, Statistics, Advertising, Web Analytics, and more.

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LinkedIn is testing Microsoft's AI art generator to design your posts. Here's how it works

Thomas Trutschel/Contributor/Getty Images

LinkedIn posts are a great way to showcase your latest career accomplishments with your network. However, LinkedIn feeds are so saturated with posts that it can take time to stand out. AI is here to help with that.

Also: These are my 5 favorite AI tools for work

A post shared on X, formerly known as Twitter, by a beta user shows that LinkedIn is testing the integration of Microsoft Designer on its platform. With the integration, users will be able to create unique visual assets within LinkedIn.

Microsoft Designer is Microsoft's take on Canva, a graphic design platform that can be used to create everything from social media posts to presentations, and even company branding. The major difference is that Designer leverages AI.

Microsoft's take on a graphic design platform uses generative AI throughout its platform to enable users to create anything they want by simply using text. LinkedIn is testing adding those abilities to its platform to help users create original posts without leaving the app.

Also: How AI can turn any photo into a professional headshot

As shown by the video attached to the X post, LinkedIn users would have the opportunity to add an image and have Designer incorporate it into an original with a simple text prompt.

The instructions can include as much or as little detail including colors, the motif, and purpose. Once the prompt is finalized, Designer will generate multiple renditions within the platform, facilitating the posting process.

LinkedIn has quickly adopted AI on its platform, unveiling several AI features including AI-generated recruiter messages, profile sections, copy suggestions for ads, and even post generation. If LinkedIn continues to keep up its current pace, they can expect to see this integration soon.

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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