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 : PCAP-31-03
Exam Name : Certified Associate in Python Programming - 2023
Vendor Name : AICPA
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PCAP-31-03 exam Format | PCAP-31-03 Course Contents | PCAP-31-03 Course Outline | PCAP-31-03 exam Syllabus | PCAP-31-03 exam Objectives
EXAM CODE: PCAP-31-03
EXAM NAME: Certified Associate in Python Programming
SCORES:
Section 1 → 6 items, Max Raw Score: 12 (12%)
Section 2 → 5 items, Max Raw Score: 14 (14%)
Section 3 → 8 items, Max Raw Score: 18 (18%)
Section 4 → 12 items, Max Raw Score: 34 (34%)
Section 5 → 9 items, Max Raw Score: 22 (22%)
The test candidate who has passed the PCAP-31-03 exam demonstrates the following proficiency in Python programming:
- an ability to design, develop and Boost multi-module computer applications coded in Python
- an ability to analyze and model real-life problems in OOP categories
- experience allowing her/him to take a job as a junior developer
- sufficient skills to create and develop her/his own programming portfolio
- the potential to use Python in everyday life applications including DIY activities
Section 1: Modules and Packages
Section 2: Exceptions
Section 3: Strings
Section 4: Object-Oriented Programming
Section 5: Miscellaneous
Modules and Packages (12%)
PCAP-31-03 1.1 – Import and use modules and packages
import variants: import, from import, import as, import *
advanced qualifying for nested modules
the dir() function
the sys.path variable
PCAP-31-03 1.2 – Perform evaluations using the math module
functions: ceil(), floor(), trunc(), factorial(), hypot(), sqrt()
PCAP-31-03 1.3 – Generate random values using the random module
functions: random(), seed(), choice(), sample()
PCAP-31-03 1.4 – Discover host platform properties using the platform module
functions: platform(), machine(), processor(), system(), version(), python_implementation(), python_version_tuple()
PCAP-31-03 1.5 – Create and use user-defined modules and packages
idea and rationale;
the __pycache__ directory
the __name__ variable
public and private variables
the __init__.py file
searching for/through modules/packages
nested packages vs. directory trees
Exceptions (14%)
PCAP-31-03 2.1 – Handle errors using Python-defined exceptions
except, except:-except, except:-else:, except (e1, e2)
the hierarchy of exceptions
raise, raise ex
assert
event classes
except E as e
the arg property
PCAP-31-02 2.2 – Extend the Python exceptions hierarchy with self-defined exceptions
self-defined exceptions
defining and using self-defined exceptions
Strings (18%)
PCAP-31-03 3.1 – Understand machine representation of characters
encoding standards: ASCII, UNICODE, UTF-8, code points, escape sequences
PCAP-31-03 3.2 – Operate on strings
functions: ord(), chr()
indexing, slicing, immutability
iterating through strings, concatenating, multiplying, comparing (against strings and numbers)
operators: in, not in
PCAP-31-03 3.3 – Employ built-in string methods
methods: .isxxx(), .join(), .split(), .sort(), sorted(), .index(), .find(), .rfind()
Object-Oriented Programming (34%)
PCAP-31-03 4.1 – Understand the Object-Oriented approach
ideas and notions: class, object, property, method, encapsulation, inheritance, superclass, subclass, identifying class components
PCEP-31-03 4.2 – Employ class and object properties
instance vs. class variables: declarations and initializations
the __dict__ property (objects vs. classes)
private components (instances vs. classes)
name mangling
PCAP-31-03 4.3 – Equip a class with methods
declaring and using methods
the self parameter
PCAP-31-03 4.4 – Discover the class structure
introspection and the hasattr() function (objects vs classes)
properties: __name__, __module__ , __bases__
PCAP-31-03 4.5 – Build a class hierarchy using inheritance
single and multiple inheritance
the isinstance() function
overriding
operators:
not is
, is
polymorphism
overriding the __str__() method
diamonds
PCAP-31-03 4.6 – Construct and initialize objects
declaring and invoking constructors
Miscellaneous (22%)
PCAP-31-03 5.1 – Build complex lists using list comprehension
list comprehensions: the if operator, nested comprehensions
PCAP-31-03 5.2 – Embed lambda functions into the code
lambdas: defining and using lambdas
self-defined functions taking lambdas as arguments
functions: map(), filter()
PCAP-31-03 5.3 – Define and use closures
closures: meaning and rationale
defining and using closures
PCAP-31-03 5.4 – Understand basic Input/Output terminology
I/O modes
predefined streams
handles vs. streams
text vs. binary modes
PCAP-31-03 5.5 – Perform Input/Output operations
the open() function
the errno variable and its values
functions: close(), .read(), .write(), .readline(), readlines()
using bytearray as input/output buffer
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How Crying Can Help You, Here Is What A Study SaysGettyThey say that there's no sense in crying over spilled milk. But what do they know? Crying can get you another glass of milk if you do it loud enough. Plus, crying may serve a real physiologic purpose, according to a study published recently in Emotion, meaning the journal and not in an Emo-kind of way. For the study, three researchers from the University of Queensland (Leah S. Sharman, Genevieve A. Dingle, and Eric J. Vanman) and one from Tilberg University (Ad J. J. M. Vingerhoets) recruited 197 female undergraduate students. They said that they choose all women rather than including men because pilot testing of sad videos had revealed that more women than men cried or at least more women revealed that they were crying. This did not account for the men who cried inside or used some bro-language or high fives to hide the crying. The research team then showed each of the study participants either a video that are supposed to make them feel sad (sad videos) or a video that was not supposed to elicit any emotion (neutral videos) like something from a documentary or a ted talk. Each video lasted for close to 18 minutes. After the video, the researchers noted whether or not each participant had cried while watching the video. Ultimately, 65 participants watched the neutral video, 71 watched the sad video and cried during it, and 61 watched the sad video and did not cry. Presumably, no one cried during the neutral video. But then again, actor Bryce Dallas Howard was able to cry when Conan O'Brien talked about Home Depot in this Conan clip: Then, each participant underwent a Cold Pressor Stress Test (CPT), which involved placing the participant's left hand, up to the wrist, in cold 0° to 5°C water. Unless you are the Iceman or Killer Frost, this is supposed to be painful. The research team measured how long each participant could stay in this position until pulling her hand out of the water. During the study, the research team continuously measured each participant's heart rate and respiratory rate and periodically measured cortisol levels from saliva samples. Cortisol is a stress-hormone that's produced by the body. Also, at four points during the study, participants answered questions from the Positive and Negative Affect Scale short form (PANAS). These questions asked the degree to which the participant was experiencing ten different emotions and to rank each on a five-point scale that ranged from a one (very slightly or not at all) to a five (extremely). When it came to cortisol levels and how long the participants could keep their hands submerged in the cold water, the study ended up finding not much difference between the neutral video watchers, the sad video non-criers, and the sad video criers. So if you are about to dunk yourself in cold water or take a cold shower, it may not help to cry first. But here's a difference that the study found. Are you ready? Take a deep breath. The difference was breathing rates. While watching the videos, the non-criers tended to have elevations in their breathing rates, whereas, by contrast, the criers tended to maintain their initial breathing rates. In other words, tearing up could have helped participants better control their breathing rates. This provides further evidence that crying may help you better regulate arousal, serving as an emotional release. Another interesting finding was that right before crying, participants tended to experience decreases in their heart rates, seemingly in anticipation of the crying. Once the crying began, their heart rates then tended to creep back up but not above where their heart rates had been before everything began. This may be further evidence that crying has a beneficial regulatory effect on your physiology. So perhaps next time you start crying you can tell people that you are regulating your physiology. You've probably heard of people saying that they had a good cry and feel better after they've let the tears flow. It can be important to find reasonable ways to periodically release your emotions. Otherwise, you may end up bottling everything up like a hot air balloon that can explode when you least expect it. Moreover, crying can be a way of communicating. It's really the only way that babies can express their needs before they learn how to say things like "why you throwing shade on me," or "I'm not Gucci." Crying can help communicate to others that you need more sympathy, comfort, or help. Of course, this can be misused. You don't want to cry every time your order at a restaurant doesn't come out right. And of course, there is the whole concept of crocodile tears: people crying to get something when they don't really mean it. Crying can also be a way of communicating with yourself. Even when you cry alone, you may be telling yourself about your own state because, like many people, you could be terrible at memorizing your own emotions and situation. Tears could be your body's way of saying, "hey, take a break," or "something's not right," or "take care of yourself." Tearing up can then be a way of your body literally crying out to you. Your body is a complex system. Crying can be complex. Your tears can flow when you are very sad, very angry, or even very happy. Better understanding what causes us to cry and what happens as a result could help us better handle their emotions and stress. Researchers use artificial intelligence to help diagnose autism, study saysResearchers are proposing using artificial intelligence technology to help diagnose autism spectrum disorder. In a accurate article published in Scientific Reports, researchers from Brazil, France and Germany reportedly used magnetic resonance imaging to train a machine learning algorithm. The work – in which the "quantitative diagnostic method" is proposed – was based on brain imaging data for 500 people, with more than 240 that had been diagnosed with autism. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? Machine learning techniques were applied to the data. "We began developing their methodology by collecting functional magnetic resonance imaging [fMRI] and electroencephalogram [EEG] data," Francisco Rodrigues, the last author of the article and a professor at the University of São Paulo’s Institute of Mathematics and Computer Science, explained in a statement. AS AI SHOWS UP IN DOCTORS' OFFICES, MOST PATIENTS ARE GIVING PERMISSION AS EXPERTS ADVISE CAUTION São Paulo University on November 15, 2015, in São Paulo, Brazil. (Frédéric Soltan/Corbis via Getty Images) "We compared maps of people with and without ASD and found that diagnosis was possible using this methodology," he added. The machine learning algorithm was fed with the maps, and the system was able to determine which brain alterations were associated with autism with above 95% mean accuracy. While previous research proposes methods for diagnosing autism based on machine learning, the article notes it often uses a single statistical parameter that is not brain network organization. Autism is a developmental disability caused by differences in the brain. (iStock) CALIFORNIA MAN WITH SEVERE AUTISM BEATS RUBIK'S CUBE WORLD RECORD: 'EXUBERANCE IN THEIR HEARTS' Analyzing the fMRI data showed changes in certain brain regions associated with cognitive, emotional, learning and memory processes, and the cortical networks of autism patients showed more segregation, less distribution of information and less connectivity compared to controls. "Until a few years ago, little was known about the alterations that lead to the symptoms of ASD. Now, however, brain alterations in ASD patients are known to be associated with certain behaviors, although anatomical research shows that the alterations are hard to see, making diagnosis of mild ASD much harder. Their study is an important step in the development of novel methodologies that can help us obtain a deeper understanding of this neurodivergence," Rodrigues said. The Centers for Disease Control and Prevention headquarters in Atlanta, Georgia, on March 14, 2020. (Elijah Nouvelage/Bloomberg via Getty Images) The methodology is under development and will take years to implement, according to the São Paulo Research Foundation, which supported the research. CLICK HERE TO GET THE FOX NEWS APP About one in 36 children has been identified with autism spectrum disorder, according to the Centers for Disease Control and Prevention. Diagnosing the developmental disability can be difficult because there is no medical test, like a blood test, to do so. Julia Musto is a reporter for Fox News and Fox Business Digital. |
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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