Security
2024 | AI Dictionary
What is Security in AI: The practice of protecting AI systems and data from cyber threats, unauthorized access, and malicious manipulation.
What is Security?
Security refers to safeguarding AI systems from cyber threats, unauthorized access, and malicious manipulation. It encompasses protecting the integrity, confidentiality, and availability of the AI system and its underlying data to ensure its safe and trusted operation. Securing AI is critical to preventing vulnerabilities that could lead to breaches, data theft, or misuse.
Types of Security
- Data Security: Protecting sensitive data used for training, validation, and inference from unauthorized access or alteration.
- Model Security: Safeguarding AI models from theft, reverse engineering, or adversarial attacks aimed at causing incorrect outputs.
- System Security: Ensuring the AI infrastructure, including networks and servers, is resilient to external attacks, including denial of service (DoS) or hacking attempts.
Applications of Security
- Financial Systems: AI models used for fraud detection or algorithmic trading need to be secured against manipulation or unauthorized access.
- Healthcare AI: Protecting patient data and ensuring that AI systems provide accurate, tamper-free recommendations or diagnoses.
- Autonomous Vehicles: Ensuring that self-driving car systems are protected from cyberattacks that could disrupt navigation or safety functions.
Example of Security
An AI-powered surveillance system must be secured to prevent hackers from altering its functionality, such as tampering with face recognition algorithms or accessing surveillance footage, which could compromise security operations.
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