Data Loss Prevention (DLP) for email systems helps organizations prevent sensitive data within email from being lost, leaked, or accessed by unauthorized individuals, be it an insider risk or malicious behavior from outside. Solutions for email DLP monitor inbound and outbound messages, searching for loss risks like content or attachments that are sensitive, confidential, or protected by regulation. Email DLP systems can flag, block, or delete an email based on custom policy.

As companies handle increasingly sensitive information, securing data in motion—the data actively transferred across networks or between devices—has become an important priority. Whether moving through corporate networks, across mobile devices, or stored in the cloud, this data is particularly vulnerable to threats from malicious actors, insider threats, and unauthorized users.

Email remains a critical communication channel for businesses of all sizes, but it also presents significant data security risks. Data loss prevention (DLP) for email is an essential component of any robust cybersecurity strategy that can help your organization safeguard sensitive information from accidental leaks, malicious insiders, and external threats.

Recognizing the indicators of insider risk before they turn into threats requires a paradigm shift in the way we operate. It necessitates moving from a reactive mode of operation to proactive. And it requires data that is continuously captured and analyzed to enable security teams to easily see patterns and anomalies and gauge the level of risk of specific behaviors.

You may trust the people you work and partner with, but you never know how they really behave and handle your sensitive data within your organization’s network. Each user in your IT infrastructure brings their own security risks. Tracking user activity helps mitigate those risks and enhance your organization’s security. This article will show you how to set up an efficient user activity monitoring (UAM) process with Ekran System.

Elizabeth Harz, CEO of Veriato, sits down with Chris Hughes from Acceleration Economy for an exclusive interview to discuss the evolving landscape of insider risk management.

External cybersecurity threats are a well-known problem, but organizations should also be aware of managerial insider threats. These threats originate from individuals with privileged access and authority and can cause devastating damage to an organization’s data, reputation, and bottom line. In this guide, we’ll examine managerial insider threats and offer insights and strategies you can use to detect, prevent, and mitigate these risks.

Generative AI (GenAI) tools like ChatGPT have already become indispensable across organizations worldwide. CEOs are particularly enthusiastic about GenAI’s ability to let employees “do more with less”. According to the McKinsey Global Survey on the State of AI in 2024, 65% of organizations already use GenAI tools extensively, and Gartner forecasts that this number will reach 80% by 2026.

A company’s success depends on its employees’ quality, motivation, and honesty. Unmotivated employees who feel neglected and under-appreciated may not hesitate to deceive their employer for their own personal benefit. This type of fraud is known as occupational fraud, and it’s a growing concern for business leaders. So, how can employers detect and prevent this type of fraud from happening?

Is your company grappling with an increasing volume and complexity of information? A strong data governance framework is essential to harness the power of data while lessening risks. This strategic framework ensures data is managed effectively, meets quality standards, and supports informed decision-making, quality standards, and supporting informed decisions. As regulatory compliance burdens intensify, data governance has become critical to organizational success.