A security violation in the form of a data breach can create costly damage to a company's reputation. But what exactly is a data breach? The European Commission has divided data breaches into three distinct categories — confidentiality breaches, integrity breaches, and availability breaches: In this article, you'll learn more about what a data breach is and how you can prevent data breaches when designing and developing your software.

Since the onset of the pandemic in 2020, global concern for data security and privacy has skyrocketed like a dazzling display of fireworks on New Year’s Eve. With an ever-increasing number of people utilizing online services and sharing their personal information on websites to engage in e-commerce transactions, the infrastructure for collecting and safeguarding consumer data has become of paramount importance.

When a hacker breaches a network or system, data exfiltration often follows. But what is data exfiltration and how can you prevent it?

Generative Artificial Intelligence (AI) has revolutionized various fields, from creative arts to content generation. However, as this technology becomes more prevalent, it raises important considerations regarding data privacy and confidentiality. In this blog post, we will delve into the implications of Generative AI on data privacy and explore the role of Data Leak Prevention (DLP) solutions in mitigating potential risks.

Cyber threats are a growing concern for organizations of all sizes. Data breaches, malware infections, and ransomware attacks can severely disrupt operations, including financial loss, reputational damage, and legal liabilities. As a result, it is essential to proactively monitor your environment and identify malicious activity to detect threats before they can cause significant damage.

There’s no denying it, public cloud is here to stay and there’s a pretty good chance that your company is running some workloads on Amazon Web Services.