Artificial Intelligence is revolutionizing virtually all industries, but it also brings with it a unique set of security challenges. In our recent webinar, “Innovation Unleashed: Navigating Emerging Technologies” we explored the unique juxtaposition that is AI for security, and security for AI.
"AI has the potential to significantly enhance security measures, but at the same time, it introduces new vulnerabilities that require robust security solutions tailored to AI systems," says Cisco Investments Senior Director Prasad Parthasarathi, who leads our security investments and acquisitions.
Enterprises looking to deploy AI security solutions can’t do so without understanding the critical balance between innovation and risk management.
"Privacy and security are the top concerns for everyone. Organizations are trying to figure out how this new technology will fit into the enterprise and where it can bring benefits without compromising their security posture," emphasizes Yaron Singer, Vice President, Cisco Security Business Group.
During the webinar, we hosted two of our AI investments, Query and Securiti, to showcase how their innovative solutions address the security challenges enterprises face when integrating AI into their systems.
Here are the top takeaways from their presentations.
AI for Security
One of the major challenges enterprises face is managing and analyzing the vast, fragmented security data generated across multiple tools and systems. Without a unified way to access and interpret this information, critical insights can be missed, and threats may go undetected. To address this, Query’s federated search solution acts as a powerful search engine for security data, integrating seamlessly with existing IT infrastructure. This capability enables security analysts to access and analyze data efficiently without the complexity and security risks associated with moving it.
"We've built a cloud SaaS hosted platform that integrates through APIs into the data sources that you already have in your environment," explained Matt Eberhart, CEO of Query.
By normalizing search queries and results across various data sources, Query makes it easier for enterprises to get comprehensive insights.
Moreover, Query leverages AI to enhance its search capabilities, providing intelligent summarization and insights from large datasets. This AI-powered approach helps security teams quickly understand complex data sets and make informed decisions.
"We know exactly what API call to make. Searching so surgically also controls costs. Most of our searches are fractions of a penny," he added.
Security for AI
Query leverages AI to access and analyze pertinent information without the hassle of data movement or centralization. However, as enterprises expand their AI capabilities, the question arises: who is securing the AI itself? Effective AI deployment necessitates governed data access to ensure privacy, compliance, and security at every stage. Without proper governance, AI models cannot fully leverage enterprise data, limiting their potential and increasing risks.
Securiti provides a comprehensive AI security framework that ensures governed data access, privacy, and compliance.
"Even if you bring the best model into the enterprise, frankly, you can't do much with it. Why? Because until these models actually have access to your data—and not just simple access but governed access—you can't fully leverage them," explains Rehan Jalil, CEO of Securiti.
This comprehensive approach goes beyond securing the AI model to encompass the entire AI system and all the controls that need to be in place.
"The security for AI is not just security for the AI model. It is for the entire AI system and all the controls that need to be there across the system," Jalil emphasized.
If you’re interested in learning more, you can watch the full webinar featuring Query and Securiti on demand, here.