As artificial intelligence (AI) systems become integral to business operations, understanding the security threats associated with these technologies is essential. AI security encompasses practices designed to protect these systems from unauthorised access, tampering, and malicious attacks. In fact, according to IBM1, organisations without AI security face an average data breach cost of USD 5.36 million, which is 18.6% higher than the average cost for all organisations.
What are the Types of AI Security Threats?
As AI systems become integral to business operations, they introduce unique vulnerabilities that traditional security measures may not fully address. From data manipulation to model exploitation, these threats can compromise the integrity, confidentiality, and reliability of AI-driven processes. Here are some of the key threats AI systems are at risk from.
| Threat Type | Attack Method |
|---|---|
| Data Poisoning | Injecting misleading data into training datasets to distort model learning. |
| Model Theft | Reverse-engineering proprietary AI models to expose intellectual property. |
| Input Manipulation | Subtly altering input data to produce incorrect AI outputs. |
| Privacy Breaches | Compromising sensitive data processed by AI systems. |
| Evasion Attacks | Manipulating input data to bypass detection or classification. |
| Model Exfiltration | Extracting model architecture or data through side-channel attacks. |
| Sensitive Model Outputs | AI models unintentionally revealing confidential information. |
| Prompt Injection Attacks | Manipulating prompts to force harmful or unintended AI model outputs. |
As AI systems become integral to business operations, they introduce unique vulnerabilities that traditional security measures may not fully address. Prevention is better than cure—that’s why it’s crucial to discover and understand the incidents and potential threats an AI system may face should your organisation adopt it. Recognising these threats is one of the steps in securing AI systems, and AIQURIS provides a comprehensive approach to identifying and mitigating AI security risks across the entire AI lifecycle—from development to deployment.
Key Security Attributes in AI
In ensuring trustworthy AI deployment, it is crucial to consider key attributes defined by ISO/IEC 25059:2023, specifically under the "AI System Quality Model". This standard outlines vital characteristics including:
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Confidentiality: Ensuring data is accessible only to authorised entities.
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Integrity: Maintaining the accuracy and reliability of data and system operations.
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Non-repudiation: Preventing denial of actions or transactions by involved parties.
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Accountability: Tracing AI system actions back to responsible entities.
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Authenticity: Verifying the legitimacy of users, data, and system components.
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Intervenability: Allowing human oversight over AI decisions.
These attributes support broader AI risk pillars, particularly in governance and security, playing a critical role in protecting against AI security threats.
Strategies for Mitigating AI Security Risks
To defend against AI security threats, organisations should adopt a multi-faceted approach:
| Strategy | Description |
|---|---|
| Rigorous Data Validation | Implement checks on data integrity before it enters training pipelines.3 |
| Regular Algorithm Audits | Continuously monitor AI models for performance degradation and interference point.2 |
| Robust Access Controls | Limit access to sensitive AI systems through advanced permission management.2 |
| Encryption and Secure Communication | Use robust encryption for data at rest and in transit, rotating keys regularly.4 |
| Zero-Trust Architecture | Continuously verify users and devices accessing AI systems to minimise risks.3 |
| Explainability & Transparency | Use interpretable models to enhance trust and detect potential vulnerabilities.5 |
| Incident Response Planning | Develop protocols and conduct drills for AI-related threats and post-incident analysis.2 |
As AI continues to transform business landscapes, ensuring the safe and compliant deployment of AI solutions is crucial. At AIQURIS, our team of experts specialises in AI risk and quality management, providing comprehensive support to empower your organisation's AI journey.
Talk to an AIQURIS expert today to discover how our tailored strategies and solutions can help you navigate the complexities of AI adoption, ensuring your business remains ahead of the curve while maintaining the highest standards of safety, security, and regulatory compliance.
