📌 AI Security Strategy Summary
AI security strategy refers to the planning and measures taken to protect artificial intelligence systems from threats, misuse, or failures. This includes identifying risks, setting up safeguards, and monitoring AI behaviour to ensure it operates safely and as intended. A good AI security strategy helps organisations prevent data breaches, unauthorised use, and potential harm caused by unintended AI actions.
🙋🏻♂️ Explain AI Security Strategy Simply
Think of an AI security strategy like setting up security cameras, locks, and rules for a smart robot in your house. You want to make sure it does what you say, keeps your secrets safe, and cannot be tricked or hacked. Just as you would not leave your front door open, you should not let AI run without protection.
📅 How Can it be used?
Integrate regular security audits and access controls when deploying AI models in a healthcare application.
🗺️ Real World Examples
A financial services company uses an AI security strategy to protect its fraud detection system from being manipulated by cybercriminals. They include strict access controls, monitor for unusual activity, and regularly update their defences to prevent attackers from learning how the AI makes decisions.
A hospital implements an AI security strategy to ensure its diagnostic AI cannot be accessed by unauthorised staff or modified by outside hackers, protecting sensitive patient data and ensuring reliable medical results.
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Knowledge graph completion is the process of filling in missing information or relationships within a knowledge graph. A knowledge graph is a structured network of facts, where entities like people, places, or things are connected by relationships. Because real-world data is often incomplete, algorithms are used to predict and add missing links or facts, making the graph more useful and accurate.
On-Policy Reinforcement Learning
On-policy reinforcement learning is a method where an agent learns to make decisions by following and improving the same policy that it uses to interact with its environment. The agent updates its strategy based on the actions it actually takes, rather than exploring alternative possibilities. This approach helps the agent gradually improve its behaviour through direct experience, using feedback from the outcomes of its own choices.
Daily Limits
Daily limits are rules that set a maximum amount or number of actions that can be performed in a single day. These limits are often used to control spending, manage usage, or maintain security. They help prevent misuse, overspending, or excessive access within a short time frame.
Secure DNS Resolution
Secure DNS resolution is a method of ensuring that when a computer looks up the address of a website, the process is protected from spying, tampering, or redirection by attackers. This is achieved by encrypting the communication between your device and the DNS server, which translates website names into numerical addresses. Secure DNS resolution helps prevent threats like man-in-the-middle attacks and blocks attempts to redirect users to malicious sites.
Deceptive Security Traps
Deceptive security traps are security measures designed to mislead attackers and detect unauthorised activity. These traps often mimic real systems, files, or data to attract attackers and study their behaviour. By interacting with these traps, attackers reveal their methods and intentions, allowing defenders to respond more effectively.