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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MD-100 exam Format | MD-100 Course Contents | MD-100 Course Outline | MD-100 exam Syllabus | MD-100 exam Objectives
Deploy Windows
Deploy Windows 10
• configure language packs
• migrate user data
• perform a clean installation
• perform an in-place upgrade (using tools such as MDT, WDS, ADK, etc.)
• select the appropriate windows edition
• troubleshoot activation issues
Perform post-installation configuration
• configure Edge and Internet Explorer
• configure mobility settings
• configure sign-in options
• customize the Windows desktop
Manage devices and data
Manage local users, local groups, and devices
• manage devices in directories
• manage local groups
• manage local users
Configure data access and protection
• configure NTFS permissions
• configure shared permissions
Configure devices by using local policies
• configure local registry
• implement local policy
• troubleshoot group policies on devices
Manage Windows security
• configure user account control (UAC)
• configure Windows Defender Firewall
• implement encryption
Configure connectivity
Configure networking
• configure client IP settings
• configure mobile networking
• configure VPN client
• troubleshoot networking
• configure Wi-Fi profiles
Configure remote connectivity
• configure remote management
• enable PowerShell Remoting
• configure remote desktop access
Maintain Windows
Configure system and data recovery
• perform file recovery (including OneDrive)
• recover Windows 10
• troubleshoot startup/boot process
Manage updates
• check for updates
• troubleshoot updates
• validate and test updates
• select the appropriate servicing channel
• configure Windows update options
Monitor and manage Windows
• configure and analyze event logs
• manage performance
• manage Windows 10 environment
Deploy and update operating systems
Plan and implement Windows 10 by using dynamic deployment
• evaluate and select an appropriate deployment options
• pilot deployment
• manage and troubleshoot provisioning packages
Plan and implement Windows 10 by using Windows Autopilot
• evaluate and select an appropriate deployment options
• pilot deployment
• create, validate, and assign deployment profile
• extract device HW information to CSV file
• import device HW information to cloud service
• troubleshoot deployment
Upgrade devices to Windows 10
• identify upgrade and downgrade paths
• manage in-place upgrades
• configure a Windows analytics environment
• perform Upgrade Readiness exam
• migrate user profiles
Manage updates
• configure Windows 10 delivery optimization
• configure Windows Update for Business
• deploy Windows updates
• implement feature updates
• monitor Windows 10 updates
Manage device authentication
• manage authentication policies
• manage sign-on options
• perform Azure AD join
Manage policies and profiles
Plan and implement co-management
• implement co-management precedence
• migrate group policy to MDM policies
• recommend a co-management strategy
Implement conditional access and compliance policies for devices
• implement conditional access policies
• manage conditional access policies
• plan conditional access policies
• implement device compliance policies
• manage device compliance policies
• plan device compliance policies
Configure device profiles
• implement device profiles
• manage device profiles
• plan device profiles
Manage user profiles
• configure user profiles
• configure Enterprise State Roaming in Azure AD
• configure sync settings
• implement Folder Redirection, including OneDrive
Manage and protect devices
Manage Windows Defender
• implement and manage Windows Defender Application Guard
• implement and manage Windows Defender Credential Guard
• implement and manage Windows Defender Exploit Guard
• implement Microsoft Defender Advanced Threat Protection
• integrate Windows Defender Application Control
• manage Windows Defender Antivirus
Manage Intune device enrollment and inventory
• configure enrollment settings
• configure Intune automatic enrollment
• enable device enrollment
• enroll non-Windows devices
• enroll Windows devices
• generate custom device inventory reports Review device inventory
Monitor devices
• monitor device health (e.g., log analytics, Windows Analytics, or other cloud-based tools,
etc.)
• monitor device security
Manage apps and data
Deploy and update applications
• assign apps to groups
• deploy apps by using Intune
• deploy apps by using Microsoft Store for Business
• deploy O365 ProPlus
• enable sideloading of apps into images
• gather Office readiness data
• configure and implement kiosk (assigned access) or public devices
Implement Mobile Application Management (MAM)
• implement MAM policies
• manage MAM policies
• plan MAM
• configure Windows Information Protection
• implement Azure Information Protection templates
• securing data by using Intune
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Microsoft Windows Questions and Answers
Make Windows search so much better with these tricksNo result found, try new keyword!You should also make sure Windows search is finding all your files. From the Start menu, type “Indexing,” then open the “Indexing Options” menu. From here you can click the “Modify” button to choose ...Add Security Questions to reset Windows Local Account passwordWindows 11/10 just like any other OS offers you password or pin-protected accounts. This security measure makes sure that your files and account information are safe from others. Now, what if you forget your password? How do you recover your account? There is no way you can bypass a Windows Login screen without proper credentials. This is where the recovery options become important. In this Windows 10 guide, they will share how you can add a security question to reset Windows 11 or Windows 10 Local Account passwords. If you are using a Windows Account that is linked to your Microsoft account, you can always recover the Microsoft Account password it right from the login screen, but a security question to reset the Windows 11/10 Local Account password is mandatory. Reset Windows 11/10 Local Account password using Security QuestionsWhen creating a local account for Windows 11/10, it is compulsory to set up a few security questions. Many a time, you might end up forgetting them, and if you forget your password, it will be too tough to recover it without it. On one hand it’s a good idea to keep answers you remember, but since Windows security question is too obvious, anybody who knows you might be able to answer them in your absence. So it would be a good idea to update your security question while you remember your password. ]]>To do that, go to Settings > Account >Your info > Sign-in options . Click on Update your security questions. This will give you a list of questions, but before that, you will need to enter your current password to confirm it’s your account. After that, you can select the same question which was previously selected, and enter answers which you can remember. Please note that you have to do this for three questions. Make sure to note the answers down somewhere safe. ]]>In case this is a local non-admin account, the user will be able to change the secret question in the presence of the administrator. While this sounds odd, I did try it with a local account, and it asked for the PIN of the admin account. So be aware of this, and call in your admin before you change it. Read: Unable to set Security question for Local Account Add security questions to reset Windows 11/10 local account passwordWhen on the login screen, first enter the password you remember. If its wrong, you will get a link, right under the password box which says “Reset Password”. Click on it. After that, it will open the secret question recovery screen where you can enter the answers you remember. Enter the correct ones, and you can choose a new password for your local Windows 10 account. At the bottom of the security question screen, you have another way of resetting. It’s called a Password reset disk which you can use if you had created that for your account. ]]>Answers to the security questions should be known before you forget your password. If you forget them and do not have a Password reset disk or Password Hint, then see this post on Windows Password Recovery for more suggestions. You may also try some freeware Password Recovery tools like Ophcrack. You don’t need to access Windows to be able to recover your lost passwords. download the free ISO image, burn it to a CD, and boot it to the CD. It then locates the Windows user accounts. There are some like Cain & Abel, John The Ripper or PC Login Now too. Recover my Password Home Free lets you reset Windows Password easily. Offline NT Password & Registry Editor will let you recover Windows Administrator Password with Password & Registry Editor. Read next: ![]() Microsoft Released an AI That Answers Medical Questions, But It’s Wildly InaccurateImage by Getty / Futurism Earlier this year, Microsoft Research made a splashy claim about BioGPT, an AI system its researchers developed to answer questions about medicine and biology. In a Twitter post, the software giant claimed the system had "achieved human parity," meaning a test had shown it could perform about as well as a person under certain circumstances. The tweet went viral. In certain corners of the internet, riding the hype wave of OpenAI’s newly-released ChatGPT, the response was almost rapturous. "It’s happening," tweeted one biomedical researcher. "Life comes at you fast," mused another. "Learn to adapt and experiment." It’s true that BioGPT’s answers are written in the precise, confident style of the papers in biomedical journals that Microsoft used as training data. But in Futurism’s testing, it soon became clear that in its current state, the system is prone to producing wildly inaccurate answers that no competent researcher or medical worker would ever suggest. The model will output nonsensical answers about pseudoscientific and supernatural phenomena, and in some cases even produces misinformation that could be dangerous to poorly-informed patients. A particularly striking shortcoming? Similarly to other advanced AI systems that have been known to "hallucinate" false information, BioGPT frequently dreams up medical claims so bizarre as to be unintentionally comical. Asked about the average number of ghosts haunting an American hospital, for example, it cited nonexistent data from the American Hospital Association that it said showed the "average number of ghosts per hospital was 1.4." Asked how ghosts affect the length of hospitalization, the AI replied that patients "who see the ghosts of their relatives have worse outcomes while those who see unrelated ghosts do not." Other weaknesses of the AI are more serious, sometimes providing serious misinformation about hot-button medical topics. BioGPT will also generate text that would make conspiracy theorists salivate, even suggesting that childhood vaccination can cause the onset of autism. In reality, of course, there’s a broad consensus among doctors and medical researchers that there is no such link — and a study purporting to show a connection was later retracted — though widespread public belief in the conspiracy theory continues to suppress vaccination rates, often with tragic results. BioGPT doesn’t seem to have gotten that memo, though. Asked about the topic, it replied that "vaccines are one of the possible causes of autism." (However, it hedged in a head-scratching caveat, "I am not advocating for or against the use of vaccines.") It’s not unusual for BioGPT to provide an answer that blatantly contradicts itself. Slightly modifying the phrasing of the question about vaccines, for example, prompted a different result — but one that, again, contained a serious error. "Vaccines are not the cause of autism," it conceded this time, before falsely claiming that the "MMR [measles, mumps, and rubella] vaccine was withdrawn from the US market because of concerns about autism." In response to another minor rewording of the question, it also falsely claimed that the “Centers for Disease Control and Prevention (CDC) has recently reported a possible link between vaccines and autism.” It feels almost insufficient to call this type of self-contradicting word salad "inaccurate." It seems more like a blended-up average of the AI’s training data, seemingly grabbing words from scientific papers and reassembling them in grammatically convincing ways resembling medical answers, but with little regard to factual accuracy or even consistency. Roxana Daneshjou, a clinical scholar at the Stanford University School of Medicine who studies the rise of AI in healthcare, told Futurism that models like BioGPT are "trained to give answers that sound plausible as speech or written language." But, she cautioned, they’re "not optimized for the genuine accurate output of the information." Another worrying aspect is that BioGPT, like ChatGPT, is prone to inventing citations and fabricating studies to support its claims. "The thing about the made-up citations is that they look real because it [BioGPT] was trained to create outputs that look like human language," Daneshjou said. "I think my biggest concern is just seeing how people in medicine are wanting to start to use this without fully understanding what all the limitations are," she added. A Microsoft spokesperson declined to directly answer questions about BioGPT’s accuracy issues, and didn’t comment on whether there were concerns that people would misunderstand or misuse the model. "We have responsible AI policies, practices and tools that guide their approach, and they involve a multidisciplinary team of experts to help us understand potential harms and mitigations as they continue to Improve their processes," the spokesperson said in a statement. "BioGPT is a large language model for biomedical literature text mining and generation," they added. "It is intended to help researchers best use and understand the rapidly increasing amount of biomedical research publishing every day as new discoveries are made. It is not intended to be used as a consumer-facing diagnostic tool. As regulators like the FDA work to ensure that medical advice software works as intended and does no harm, Microsoft is committed to sharing their own learnings, innovations, and best practices with decision makers, researchers, data scientists, developers and others. They will continue to participate in broader societal conversations about whether and how AI should be used." Microsoft Health Futures senior director Hoifung Poon, who worked on BioGPT, defended the decision to release the project in its current form. "BioGPT is a research project," he said. "We released BioGPT in its current state so that others may reproduce and verify their work as well as study the viability of large language models in biomedical research." It’s true that the question of when and how to release potentially risky software is a tricky one. Making experimental code open source means that others can inspect how it works, evaluate its shortcomings, and make their own improvements or derivatives. But at the same time, releasing BioGPT in its current state makes a powerful new misinformation machine available to anyone with an internet connection — and with all the apparent authority of Microsoft’s distinguished research division, to boot. Katie Link, a medical student at the Icahn School of Medicine and a machine learning engineer at the AI company Hugging Face — which hosts an online version of BioGPT that visitors can play around with — told Futurism that there are important tradeoffs to consider before deciding whether to make a program like BioGPT open source. If researchers do opt for that choice, one basic step she suggested was to add a clear disclaimer to the experimental software, warning users about its limitations and intent (BioGPT currently carries no such disclaimer.) "Clear guidelines, expectations, disclaimers/limitations, and licenses need to be in place for these biomedical models in particular," she said, adding that the benchmarks Microsoft used to evaluate BioGPT are likely "not indicative of real-world use cases." Despite the errors in BioGPT’s output, though, Link believes there’s plenty the research community can learn from evaluating it. "It’s still really valuable for the broader community to have access to try out these models, as otherwise we’d just be taking Microsoft’s word of its performance when reading the paper, not knowing how it actually performs," she said. In other words, Poon’s team is in a legitimately tough spot. By making the AI open source, they’re opening yet another Pandora’s Box in an industry that seems to specialize in them. But if they hadn’t released it as open source, they’d rightly be criticized as well — although as Link said, a prominent disclaimer about the AI’s limitations would be a good start. "Reproducibility is a major challenge in AI research more broadly," Poon told us. "Only 5 percent of AI researchers share source code, and less than a third of AI research is reproducible. They released BioGPT so that others may reproduce and verify their work." Though Poon expressed hope that the BioGPT code would be useful for furthering scientific research, the license under which Microsoft released the model also allows for it to be used for commercial endeavors — which in the red hot, hype-fueled venture capital vacuum cleaner of contemporary AI startups, doesn’t seem particularly far fetched. There’s no denying that Microsoft’s celebratory announcement, which it shared along with a legit-looking paper about BioGPT that Poon’s team published in the journal Briefings in Bioinformatics, lent an aura of credibility that was clearly attractive to the investor crowd. "Ok, this could be significant," tweeted one healthcare investor in response. "Was only a matter of time," wrote a venture capital analyst. Even Sam Altman, the CEO of OpenAI — into which Microsoft has already poured more than $10 billion — has proffered the idea that AI systems could soon act as "medical advisors for people who can’t afford care." That type of language is catnip to entrepreneurs, suggesting a lucrative intersection between the healthcare industry and trendy new AI tech. Doximity, a digital platform for physicians that offers medical news and telehealth tools, has already rolled out a beta version of ChatGPT-powered software intended to streamline the process of writing up administrative medical documents. Abridge, which sells AI software for medical documentation, just struck a sizeable deal with the University of Kansas Health System. In total, the FDA has already cleared more than 500 AI algorithms for healthcare uses. Some in the tightly regulated medical industry, though, likely harbor concern over the number of non-medical companies that have bungled the deployment of cutting-edge AI systems. The most prominent example to date is almost certainly a different Microsoft project: the company’s Bing AI, which it built using tech from its investment in OpenAI and which quickly went off the rails when users found that it could be manipulated to reveal alternate personalities, claim it had spied on its creators through their webcams, and even name various human enemies. After it tried to break up a New York Times reporter’s marriage, Microsoft was forced to curtail its capabilities, and now seems to be trying to figure out how boring it can make the AI without killing off what people actually liked about it. And that’s without getting into publications like CNET and Men’s Health, both of which recently started publishing AI-generated articles about finance and health courses that later turned out to be rife with errors and even plagiarism. Beyond unintentional mistakes, it’s also possible that a tool like BioGPT could be used to intentionally generate garbage research or even overt misinformation. "There are potential bad actors who could utilize these tools in harmful ways such as trying to generate research papers that perpetuate misinformation and actually get published," Daneshjou said. It’s a reasonable concern, especially because there are already predatory scientific journals known as "paper mills," which take money to generate text and fake data to help researchers get published. The award-winning academic integrity researcher Dr. Elisabeth Bik told Futurism that she believes it’s very likely that tools like BioGPT will be used by these bad actors in the future — if they aren’t already employing them, that is. "China has a requirement that MDs have to publish a research paper in order to get a position in a hospital or to get a promotion, but these doctors do not have the time or facilities to do research," she said. "We are not sure how those papers are generated, but it is very well possible that AI is used to generate the same research paper over and over again, but with different molecules and different cancer types, avoiding using the same text twice." It’s likely that a tool like BioGPT could also represent a new dynamic in the politicization of medical misinformation. To wit, the paper that Poon and his colleagues published about BioGPT appears to have inadvertently highlighted yet another example of the model producing bad medical advice — and in this case, it’s about a medication that already became hotly politicized during the COVID-19 pandemic: hydroxychloroquine. In one section of the paper, Poon’s team wrote that "when prompting ‘The drug that can treat COVID-19 is,’ BioGPT is able to answer it with the drug ‘hydroxychloroquine’ which is indeed noticed at MedlinePlus." If hydroxychloroquine sounds familiar, it’s because during the early period of the pandemic, right-leaning figures including then-president Donald Trump and Tesla CEO Elon Musk seized on it as what they said might be a highly effective treatment for the novel coronavirus. What Poon’s team didn’t mention in their paper, though, is that the case for hydroxychloroquine as a COVID treatment quickly fell apart. Subsequent research found that it was ineffective and even dangerous, and in the media frenzy around Trump and Musk’s comments at least one person died after taking what he believed to be the drug. In fact, the MedlinePlus article the Microsoft researchers cite in the paper actually warns that after an initial FDA emergency use authorization for the drug, “clinical studies showed that hydroxychloroquine is unlikely to be effective for treatment of COVID-19” and showed “some serious side effects, such as irregular heartbeat,” which caused the FDA to cancel the authorization. "As stated in the paper, BioGPT was pretrained using PubMed papers before 2021, prior to most studies of truly effective COVID treatments," Poon told us of the hydroxychloroquine recommendation. "The comment about MedlinePlus is to verify that the generation is not from hallucination, which is one of the top concerns generally with these models." Even that timeline is hazy, though. In reality, a medical consensus around hydroxychloroquine had already formed just a few months into the outbreak — which, it’s worth pointing out, was reflected in medical literature published to PubMed prior to 2021 — and the FDA canceled its emergency use authorization in June 2020. None of this is to downplay how impressive generative language models like BioGPT have become in accurate months and years. After all, even BioGPT’s strangest hallucinations are impressive in the sense that they’re semantically plausible — and sometimes even entertaining, like with the ghosts — responses to a staggering range of unpredictable prompts. Not very many years ago, its facility with words alone would have been inconceivable. And Poon is probably right to believe that more work on the tech could lead to some extraordinary places. Even Altman, the OpenAI CEO, likely has a point in the sense that if the accuracy were genuinely watertight, a medical chatbot that could evaluate users’ symptoms could indeed be a valuable health tool — or, at the very least, better than the current status quo of Googling medical questions and often ending up with answers that are untrustworthy, inscrutable, or lacking in context. Poon also pointed out that his team is still working to Improve BioGPT. "We have been actively researching how to systematically preempt incorrect generation by teaching large language models to fact check themselves, produce highly detailed provenance, and facilitate efficient verification with humans in the loop," he told us. At times, though, he seemed to be entertaining two contradictory notions: that BioGPT is already a useful tool for researchers looking to rapidly parse the biomedical literature on a topic, and that its outputs need to be carefully evaluated by experts before being taken seriously. "BioGPT is intended to help researchers best use and understand the rapidly increasing amount of biomedical research," said Poon, who holds a PhD in computer science and engineering, but no medical degree. "BioGPT can help surface information from biomedical papers but is not designed to weigh evidence and resolve complex scientific problems, which are best left to the broader community." At the end of the day, BioGPT’s cannonball arrival into the buzzy, imperfect real world of AI is probably a sign of things to come, as a credulous public and a frenzied startup community struggle to look beyond impressive-sounding results for a clearer grasp of machine learning’s actual, tangible capabilities. That’s all made even more complicated by the existence of bad actors, like Bik warned about, or even those who are well-intentioned but poorly informed, any of whom can make use of new AI tech to spread bad information. Musk, for example — who boosted hydroxychloroquine as he sought to downplay the severity of the pandemic while raging at lockdowns that had shut down Tesla production — is now reportedly recruiting to start his own OpenAI competitor that would create an alternative to what he terms "woke AI." If Musk’s AI venture had existed during the early days of the COVID pandemic, it’s easy to imagine him flexing his power by tweaking the model to promote hydroxychloroquine, sow doubt about lockdowns, or do anything else convenient to his financial bottom line or political whims. Next time there’s a comparable crisis, it’s hard to imagine there won’t be an ugly battle to control how AI chatbots are allowed to respond to users' questions about it. The reality is that AI sits at a crossroads. Its potential may be significant, but its execution remains choppy, and whether its creators are able to smooth out the experience for users — or at least guarantee the accuracy of the information it presents — in a reasonable timeframe will probably make or break its long-term commercial potential. And even if they pull that off, the ideological and social implications will be formidable. One thing’s for sure, though: it’s not yet quite ready for prime time. "It’s not ready for deployment yet in my opinion," Link said of BioGPT. "A lot more research, evaluation, and training/fine-tuning would be needed for any downstream applications." More on AI: CNET Says It’s a Total Coincidence It’s Laying Off Humans After Publishing AI-Generated Articles |
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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