Data protection and AI platform innovations

Zscaler has unified data protection across five key areas. These are: secure data-in-motion, secure SaaS data, secure cloud data, secure endpoint data, and secure BYoD.

Pradeep Chakraborty
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Data protection

Data protection and AI platform innovations.

Cutting-edge data protection AI platform enhancements that harness the power of AI to safeguard sensitive data was up next at Zscaler '24.


Moinul Khan, VP/GM, Data Protection, Zscaler, said, we have unified data protection across five key areas. These are: secure data-in-motion, secure SaaS data, secure cloud data, secure endpoint data, and secure BYoD. There is integrated workflow automation, with user coaching and escalation.

We are looking at traffic coming from workforce, workloads, IoT devices, etc. We are n the path, and looking at all the data. For zero trust exchange, we do content inspection. Contextual data protection is for zero trust exchange. This includes shadow IT and shadow AI, auto data discovery (AI driven), cloud app control (with isolation), and tenancy restrictions. We also have OCR. We have delivered hundreds of dictionaries. 

We are securing all data exfiltration channels. We have new innovations. First is DSPM. DSPM is part of your data protection platform. We have web data, device data, SaaS data, IaaS data, and private app data. You have to protect data everywhere. 


You care about your assets in your car. You need to secure your baby. That is also your data, or IP. It needs to be secure. Integrated DLP can secure structured and unstructured data in the public cloud. We need to remediate risks as fast as we can.

Kalie Radsmikham, Zscaler, took us through the DSPM dashboard. There are lots of legal documents in the dashboard. DSPM allows more holistic view of risk. We may find an EC2 that can be exposed. 

Khan next talked about GenAI app. Your enterprise data can be at risk. There can be data risk for financial data, as well. There can be risky apps. You cannot block every single app. You need to have workflow automation to coach users. We can protect sensitive data from GenAI apps. These could be via GitHub Pilot, ChatGPT, and Google Gemini. It is all about implementing granular policies.


Steve Grossbacher took us through a GenAI security report. Employee and business data are two important areas to look at. 

Khan added that there are obstacles that impact data security. We have a data discovery dashboard. Lastly, we have unified SaaS security. He showed a demo of how to reduce this.

Jennifer Hunt, Head of Cyber Security Data, Blackbaud, talked about data protection. Blackbaud is an essential software provider for people and organizations that change the world. We are 100% focused on social impact. 


The next natural progression is EPA. We are now rolling out Zscaler for workloads. We want to understand where data is, who us using it, what are the vulnerabilities. On AI side, we started with Zscaker solution. Every solution has an AI component these days. We are now able to add a risk force, around apps. We are also able to provide granular control. We can implement DLP controls. 

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