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Security in Generative AI Infrastructure Is of Critical Importance
- Generative AI industry is growing, but data security and model safety are becoming a significant concern for businesses for effective and secure models.
- According to IBM's survey, 82% of respondents accepted that security in AI is essential to their business, but only 24% of projects have parts to secure the initiative.
- Data poisoning, model manipulation, prompt injection attacks, and supply chain attacks pose significant risks to GenAI infrastructure.
- To secure GenAI infrastructure, one needs to implement secure-by-design architecture that covers secure data ingestion infrastructure, data manipulation operations, model deployment, and user interaction.
- Supply chain attacks are more complex to prevent, but digitally signing all pieces, and pieces and validation before deployment can be a good start.
- It's important to secure customer data to protect users' trust as the conversations are between a human and a machine, and the personal nature of such discussions should be treated like human-to-human conversations.
- Security is not an add-on, it should be weaved in and through the entire infrastructure rather than just being slapped on top of it to pass regulations and compliance.
- Individuals themselves need to become security champions and create a culture shift for better security practices in the GenAI industry.
- Moving forward with GenAI innovation while sidelining security is equivalent to playing with fire, resulting in disastrous consequences such as lost customer trust, personal data leak, and government-imposed penalties.
- Organizations and individuals who recognize the importance of security in GenAI and act proactively will be best positioned to thrive and overcome dangers and regulatory hurdles.
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