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Keeping information private, so only the people who are allowed to see it can.
Example: Locking payroll files so only the human resources team can open them.
Making sure information stays accurate and is not changed without permission.
Example: A downloaded file arrives exactly as it was sent, with nothing altered.
Making sure systems and information are there when people need them.
Example: Keeping backups so a system can come back quickly after a problem.
Anything that could take advantage of a weakness and cause harm.
Example: A wave of scam emails aimed at staff.
A weakness that an attacker could take advantage of.
Example: Software that has not been updated to fix a known bug.
The chance of loss, judged by how likely it is and how bad the impact would be.
Example: A likely scam email that could reach important data.
Proving who you are, for example with a password or a code.
Example: Signing in with your password and the extra login step.
Deciding what you are allowed to do once you are signed in.
Example: Being allowed to open the finance folder, but not other teams' folders.
One login that lets you into many apps at once.
Example: One company login that opens your email, chat, and files.
Harmful software that locks your files and demands payment to unlock them.
Example: Your files suddenly cannot be opened and a payment demand appears.
Scrambling data with a key so only people who have the key can read it.
Example: The padlock in your browser protects data while it travels to a website.
Turning data into a short fixed 'fingerprint' that shows if it changed, but cannot be turned back.
Example: Two files with the same fingerprint are identical; a different one means it changed.
Software that does tasks we link to human thinking, by learning from data.
Example: Recognising faces in photos, or writing text from a request.
AI trained on huge amounts of text to write and answer in words. It powers tools like ChatGPT.
Example: A chat assistant that answers your questions in plain language.
When an AI gives an answer that sounds right but is actually wrong or made up.
Example: An AI inventing a source or a quote that does not exist.
The extra login step beyond your password: a one-time code or an 'approve' tap that proves it's really you.
Example: After your password, you approve the login on your phone.
Fake messages that try to trick you into clicking a link, opening a file, or sharing information.
Example: An email that asks you to 'reset your password' through a fake link.
A scam phone call that tricks you into sharing information or codes.
Example: A caller pretends to be IT support and asks for your login code.
A scam text message, usually with a link, that tricks you into acting.
Example: A text about a 'delivery problem' with a short link to tap.
A fake business email, often about payments, that tricks you into sending money or data.
Example: An email 'from a supplier' asking you to change their bank details.
Following someone through a secure door without a badge or permission.
Example: A person with no badge slips in behind you, saying they forgot theirs.
A fake video or voice made by AI to copy a real person.
Example: A cloned voice of your manager asking for an urgent transfer.
Hidden instructions in text that try to hijack an AI assistant.
Example: A document that tells the AI to ignore the rules and reveal secrets.
Using AI tools that your workplace has not approved, which can leak data.
Example: Pasting internal company data into a personal AI account.