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ICT (Information and Communication Technology)

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Lesson 3: Networks, Cybersecurity and Artificial Intelligence

ICT (Information and Communication Technology)

Lesson 3: Networks, Cybersecurity and Artificial Intelligence

Overview

Overview

  • Describe the network infrastructure behind the Internet and the intranet, and compare a LAN with a WAN.
  • Explain cyber threats — phishing, smishing, ransomware and social engineering — with their detection and prevention.
  • Use a generative-AI educational assistant for summarising, explaining and coding, and write an accurate prompt.
  • Verify AI output, recognise hallucination, and keep academic integrity and intellectual-property rules.
Networks, Cybersecurity and Artificial Intelligence
├── First: computer networks and the Internet / Intranet infrastructure
│   ├── LAN characteristics
│   └── WAN characteristics
├── Second: cybersecurity and the fight against threats
│   ├── phishing and smishing
│   ├── ransomware
│   └── social engineering
└── Third: generative AI, cloud computing and technology ethics
    ├── the smart educational assistant
    ├── prompt engineering
    └── verification, hallucination and plagiarism
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Learning outcomes

Learning outcomes

  • Relate a networking need to the right class of network and justify the choice.
  • Name the most common attacks, the psychological trick each one uses, and its technical prevention.
  • List the tasks an AI assistant can perform in studying, and the tasks it must not be trusted with blindly.
  • Compose a prompt that fixes role, context, task, constraints and output format.
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Key terms

Key terms

Comparison aspectMain ideaKeywords
LANLocal Area Network over a small area. WAN — Wide Area Network over large distancesLocalAreaNetworkover
Phishing / smishingcredential theft by fake e-mail or SMScredentialtheftfakemail
Ransomwaremalware that encrypts files for a paymentmalwareencryptsfilespayment
Social engineeringpsychological manipulation of people rather than of machinespsychologicalmanipulationpeoplerather
Generative AI
  • models that produce text
  • images or code in response to a prompt
modelsproducetextimages
Prompt
  • the instruction given to the model
  • prompt engineering is writing it precisely
instructiongivenmodelengineering
Hallucination
  • the model stating something false
  • or inventing references
  • with full confidence
modelstatingsomethingfalse
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First: computer networks and the Internet / intranet infrastructure

First: computer networks and the Internet / intranet infrastructure

  • Computer networks are the physical and logical infrastructure over which Internet services travel: devices, links, routers and protocols.
  • The Internet is the public open network that connects billions of users and whose content anyone may reach.
  • The intranet is a private closed network limited to the members of one institution — bank staff or school students — and cannot be entered from outside except through encrypted security clearance.
  • Both are built with the same technologies; the difference is the access policy, not the cables.
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The local area network (LAN)

The local area network (LAN)

Covers a small, limited areaone building or one campus.
Characteristics to quote in the examhigh speed, very high data-transfer rate, easy management, and strong security because the media are under one administration.
Typical usesharing printers, local files and school servers inside one site.
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The wide area network (WAN)

The wide area network (WAN)

  • Covers vast areas — cities and continents — using communication lines, satellites and submarine fibre-optic cables.
  • Costlier and harder to manage than a LAN, and generally lower in local transfer speed because of the long links and the intermediate equipment.
  • The Internet is the largest WAN; a bank linking its branches abroad runs a private WAN.
  • Comparison table for revision coverage (small / vast), speed (very high / depends on the carrier), management (one administration / several providers), cost (low / high), example (school lab / the Internet).
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Second: cybersecurity, digital privacy and fighting threats

Second: cybersecurity, digital privacy and fighting threats

  • Cybersecurity is the practice of protecting systems, networks and data from attack; digital privacy is the user’s right to control his own data.
  • Threats combine a technical vector (a link, an attachment, a vulnerable program) with a human weakness (trust, curiosity, fear) — which is why defence is partly behaviour and not only software.
  • The standard protective set strong unique passwords, multi-factor authentication, timely updates, original antivirus with an enabled firewall, downloads from official stores only, and periodic independent backups.
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Phishing and smishing

Phishing and smishing

Comparison aspectMain ideaKeywords
Phishingfake e-mails that appear to come from a bank or a famous company and contain malicious links urging the user to log in and steal his datafakemailsappearcome
Smishingthe same scheme sent by SMSsameschemesent
How to detect it
  • inspect the sender’s e-mail address carefully
  • note spelling mistakes
  • distrust urgent demands for secret data
  • and hover over links to see the real destination
inspectsendermailaddress
Correct action
  • do not click
  • do not reply
  • open the site by typing its address
  • then report the message
clickreplyopensite
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Ransomware

Ransomware

Comparison aspectMain ideaKeywords
•
  • Harmful programs that encrypt the computer’s files completely
  • the attacker then demands a money payment for the decryption key
Harmfulprogramsencryptcomputer
Entry points
  • an attachment opened from an unknown sender
  • a fake installer
  • or an un-patched vulnerability
attachmentopenedunknownsender
Prevention as laid down in the syllabus
  • keep software updated
  • never open unknown attachments
  • and take periodic backups that are stored independently (offline or in the cloud with versioning)
  • so the machine can be restored without paying
keepsoftwareupdatednever
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Social engineering

Social engineering

Comparison aspectMain ideaKeywords
•
  • The psychological manipulation of people
  • exploiting trust
  • curiosity or fear to make them disclose secret information — the human being
  • not the machine
  • is the attacked system
psychologicalmanipulationpeopleexploiting
Forms
  • a caller pretending to be technical support asking for an OTP
  • a prize message that requires “verification”
  • a fake recruiter asking for ID documents
  • tailgating into a restricted room
callerpretendingtechnicalsupport
Defence
  • verify the identity of the requester through an official channel
  • refuse to reveal codes
  • and apply the golden rule — no bank or official institution ever asks for your password or CVV/OTP
verifyidentityrequesterthrough
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Third: the smart educational assistant

Third: the smart educational assistant

Comparison aspectMain ideaKeywords
Generative AI supports learning by
  • summarising long texts
  • explaining and simplifying complex concepts
  • suggesting research ideas and outlines
  • and writing code and correcting its errors
summarisinglongtextsexplaining
Good practice
  • use it as a tutor that explains and questions you
  • not as an answer machine that writes your assignment
tutorexplainsquestionsanswer
•
  • It works with cloud computing
  • so the heavy processing runs on remote servers rather than on the student’s device
workscloudcomputingheavy
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Prompt engineering

Prompt engineering

  • The quality of the AI output depends completely on the accuracy and clarity of the prompt written for it.
  • A complete prompt states the role (“act as a physics teacher”), the context (the grade and the topic), the task (what to produce), the constraints (length, level, language) and the required format (table, bullets, numbered steps).
  • Iterate refine the prompt with feedback instead of repeating the same vague request.
  • Vague prompt → generic answer; this cause-and-effect sentence is a model answer for “explain why the output was poor”.
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Verification, credibility and anti-impersonation

Verification, credibility and anti-impersonation

  • AI answers must never be taken as established facts without checking, because models suffer from hallucination — inventing false information and even non-existent references.
  • Cross-check every fact against a trusted source a textbook, a published paper or an official site; verify each cited reference actually exists.
  • Respect intellectual-property rights and avoid academic plagiarism; disclose the use of AI tools instead of presenting generated work as your own.
  • Beware deepfakes and impersonation confirm an identity claim through a second channel before acting.
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Worked model items

Worked model items

  • “A school lab needs a fast, easily managed and secure network inside one building.” → a LAN, justified by small coverage, high transfer rate, easy administration and security.
  • “An employee received an SMS saying his card is blocked and asking for the OTP.” → smishing plus social engineering exploiting fear; the answer: never share the OTP, contact the bank through its official number.
  • “After opening an attachment, all files became unreadable with a payment note.” → ransomware; the recovery path is restoring the independent backup, not paying.
  • “Write a prompt to get a revision table of the layers of the TCP/IP model.” → role + context + task + constraints + format, e.g. “Act as an ICT teacher; for grade 1 make a four-row table with layer, its job and one protocol per layer, in 120 words.”
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Exam traps and key takeaways

Exam traps and key takeaways

💡 High-yield traps

  • LAN versus WAN is a question of coverage; speed and manageability follow from it — quote the syllabus wording.
  • An intranet is not a “smaller Internet” technically; it is the same technology with closed access.
  • Social engineering attacks the person; malware attacks the machine. Questions often ask which one is described.
  • Ransomware demands a payment for decryption; spyware steals credentials silently — different goals, different defences.
  • Backups must be independent (offline/separate) or the ransomware encrypts them too.
  • Prompt quality controls output quality — “the model is wrong” is not the expected answer for a poor result.
  • Hallucination includes invented references, not only wrong numbers.
  • Using AI is allowed; submitting generated work as your own without disclosure is plagiarism.
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