Artificial Intelligence (AI) has revolutionized numerous domains, transforming the way we live and work. Its algorithms and models have proven their mettle by outperforming traditional methods in various applications, from natural language processing to self-driving cars. However, as AI permeates our lives, it introduces new security risks that can have catastrophic consequences. A compromised model could cause car accidents, misdiagnose illnesses, jeopardize lives, create fake content in news or manipulate stocks, impacting serious financial crises.
To harness AI’s potential, while safeguarding against vulnerabilities, regular audits, adversarial testing, and transparent model development are essential. A practical framework for securing AI systems is crucial, ensuring that the future lies at the intersection of innovation and resilience. Join us as we explore the delicate balance between progress and security in the era of technological marvels.
How to read this document
- Each of the threats below has an associated category or asset, risk area, and triggers — criteria that make a given threat apply.
- You can find a summary of each threat, together with impact and examples, as well as proposed mitigations and references.
TRAINING DATA LEAKAGE
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