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Data Security

The latest News and Information on Data Security including privacy, protection, and encryption.

Nightfall Sensitive Data Protection for Email

Leverage Nightfall’s AI-native platform to pinpoint and protect PII, PCI, PHI, secrets, and credentials across SaaS and email, including Gmail. Built with AI at the core, Nightfall Sensitive Data Protection is transforming email DLP by helping security teams to… … detect sensitive data with 2x better precision and 4x fewer false positive alerts. … act swiftly by blocking or quarantining emails, or removing attachments that contain sensitive data.

Nightfall Data Exfiltration Prevention

Nightfall Data Exfiltration Prevention uses generative AI to discover sensitive data and monitor data movement across SaaS apps like Google Drive. Nightfall’s enterprise-grade data leak prevention platform offers several key benefits, such as… … complete coverage across SaaS apps and managed endpoints. … enhanced detection accuracy, leading to 4x fewer false positive alerts. … streamlined workflows, so security teams can monitor data movement and take action from within a single user-friendly console.

Nightfall SaaS Security Posture Management (SSPM)

Nightfall SaaS Security Posture Management (SSPM) offers real-time visibility into permissions and sharing settings to prevent security posture drift. Nightfall leverages generative AI (GenAI) for a dynamic and responsive management approach to SaaS security posture, which means… … unparalleled visibility into sharing and permissions settings across SaaS apps. … enhanced detection accuracy, leading to 4x fewer false positive alerts.

Building a Robust Data Quality Management Framework: A Step-by-Step Guide

Maintaining data quality is crucial for any business that depends on dependable data. Without a structure in place, organizations run the risk of making decisions based on flawed or incomplete information. To uphold data integrity and make informed decisions businesses need to establish a data quality management framework. In this article, we will delve into the steps involved in constructing such a framework.

Here's what caused the Sisense data breach-and 5 tips for preventing it

From Uber in 2016 to Okta in 2023 to Sisense in 2024, it’s evident that there’s a pattern behind the tech industry’s most devastating breaches: Data sprawl. Let’s dive into how data sprawl played a part in last week’s Sisense breach, as well as how security teams can be proactive in defending against similar attacks.

What is the difference between Information Disclosure and Data Exposure

As digital infrastructure becomes increasingly integrated into every day operations across various industries, ensuring the security of sensitive information becomes crucial for safeguarding both individuals and organizations from cyber threats. In the vast landscape of cybersecurity risks, two terms stand out: information disclosure and data exposure. Understanding these concepts is vital, as they can significantly impact trust and lead to potential repercussions.

The role of DDI solutions in optimizing smart manufacturing network infrastructures

The Fourth Industrial Revolution, or Industry 4.0, has integrated digital technologies such as the Industrial Internet of Things (IIoT), operational technology, and information technology into the heart of manufacturing.

How Next DLP Automates Data Breach Investigations with Torq Hyperautomation

The following is adapted from a conversation between Torq and Robbie Jakob-Whitworth, Cybersecurity Solutions Architect at Next DLP. Next DLP is a leading provider of insider risk and data protection solutions. Read on to learn how Robbie has used Torq Hyperautomation to automate alerts and reduce alert fatigue within his organization.

Secure Your Staff: How to Protect High-Profile Employees' Sensitive Data on the Web

Organizations are increasingly concerned about high-profile employees’ information being exposed on the deep and dark web. The CrowdStrike Counter Adversary Operations team is often asked to find fake social media accounts and personally identifiable information (PII) that might be exposed. Impersonations and leaked PII can unravel lives and ruin the reputations of individuals and their organizations.

Redact sensitive data from your logs on-prem by using Observability Pipelines

As your business evolves to serve more users, your applications and infrastructure will generate an increasing volume of logs, which may contain sensitive data such as credit card numbers, IP addresses, and tokens. When you collect sensitive data, you may be subject to laws such as GDPR—which restricts the transfer of personal data across borders, and you may face legal consequences if this data is exposed outside your infrastructure.