Cyber Solutions to Harness Potential of Generative AI

Cloud security specialist Zscaler, Inc. has released a set of advanced security solutions designed for IT and security teams to leverage the full potential of generative AI while preserving the safety of enterprises’ intellectual property and their customers’ data.

By employing its vast data pool, Zscaler utilises AI/ML or generative AI to not only predict breaches but also recommend policies to deliver superior threat detection, prevention, and response.

Zscaler operates a cloud security platform that processes more than 300 billion daily transactions from users, IoT/OT devices, workloads, and business-to-business communications.

The platform's proxy-based architecture and cloud security data lake combined with Zscaler’s Large Language Models (LLM) for secure connectivity provides a comprehensive view of an organisation's security posture while also delivering large volumes of valuable anonymised training data to continuously improve the AI models and intelligently predict breaches with precision at an unprecedented pace.

“Generative AI presents a game-changing inflection point in technology, and the organisations that have large volumes of relevant, private enterprise data to seize its potential today will emerge as leaders tomorrow,” said Jay Chaudhry, CEO, chairman and founder of Zscaler.

“Recognising the significance of this technology years ago, we’ve implemented AI and ML capabilities to dramatically improve multiple services from data protection to digital experience monitoring. Today, Zscaler is taking a quantum leap forward by introducing a suite of security capabilities that allow our customers to safely harness the power of new generative AI tools to predict and stop breaches.”

The solutions include:

Data Protection for AI - Zscaler Data Loss Prevention (DLP) prevents potential data leakage and enables organisations to record and retain content, including prompts to generative AI queries and outputs of the publicly available LLM’s and AI applications for security and audit purposes in their own environment.

AITotal - A comprehensive risk scoring system for an exploding number of AI applications, taking into account the applications’ risk profile and privacy policy.

AI Visibility & Access Control - A new URL category and cloud application specifically tailored for monitoring AI application usage. This offers the versatility to establish a variety of disparate policies for different user sets and groups, granting them precise control over access to AI applications. By implementing cloud-based Remote Browser Isolation, Zscaler provides an additional layer of security while restricting potentially hazardous actions, such as uploads, downloads, and cut-and-paste functions when accessing AI applications.

Other innovations currently in preview include:

Security Autopilot with breach prediction – A proactive approach to securing data by enabling AI engines to continuously learn from changing cloud-based policies and logs. By recommending policies and performing impact analysis, Security Autopilot simplifies security operations while helping improve security posture control and preventing future breaches. This is currently piloted by ThreatLabz, Zscaler’s advanced threat research and incident response team.

Zscaler Navigator - A simplified and unified natural language interface to enable customers to interact with Zscaler products and access relevant documentation details using a seamless, secure, and user-friendly approach.

Multi-Modal DLP - Traditional DLP solutions are limited to understanding and managing text and image-based data and the world has transitioned to a broader set of visual and audio multimedia formats. Zscaler will integrate generative AI and multi-modal capabilities into its DLP offerings to protect customers’ data from leakage across various media formats beyond text and images, such as video and audio formats. 

https://www.zscaler.com

 

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