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Conduct threat modeling exercises to help identify potential security threats to AI systems and assess their impact. Some common threats to model include data breaches, unauthorized access to systems and data, adversarial attacks and AI model bias. When you model threats and impacts, you can identify a structured approach with proactive measures to mitigate risks

Consider the following activities as part of your threat modeling:

1.Criticality

Document the business functions and objectives of each AI-driven solution, and how they relate to the criticality of your organizations operations. This helps you establish a baseline for criticality, making controls commensurate with the criticality of the AI application and determining the thoroughness of the threat model.

2.Connections

Identify the AI platforms, solutions, components, technologies and hardware, including the data inputs, processing algorithms, and output results. This will assist in identifying the logic, critical processing paths and core execution flow of the AI that will feed into the threat model and help edify the organization on the AI application.

3.Boundaries

Define system boundaries by creating a high-level architecture diagram, including components like data storage, processing, user access and communication channels. This will help you understand the AI applications data and activity footprint, threat actors and dependencies.

4.Data characteristics

Define the flows, classifications and sensitivity for the data that the AI technology will use and output. This will help determine the controls and restrictions that will apply to data flows, as you might need to pseudonymize, anonymize or prohibit certain types of data.

5.Threats

Identify potential threats for your business and technologies, like data breaches, adversarial attacks and model manipulation.

6.Impacts

Assess the potential impacts of identified threats, and assign a risk level based on vulnerability, exploitability and potential damage.

7.Mitigation

Develop and implement mitigation strategies and countermeasures to combat the identified threats, including technical measures like encryption, access controls or robustness testing, along with non-technical measures like employee training, policies or third-party audits.

8.Adaptation

Review and update the threat model on an ongoing basis as new threats emerge or as the system evolves.

Read more from the original source:
Form a strategy to mitigate cybersecurity risks in AI - Grant Thornton