The Black Vine cyberespionage group

whitePaper | February 8, 2023

In late 2022, an independent research firm completed their survey of 4,200 unbiased IT leaders and implementers on a variety of data protection drivers, challenges, and strategies — including 1175 in United States. This broad-based market study on unbiased organizations is conducted annually on Veeam’s behalf to understand how the data protection market continues to evolve, so that Veeam can ensure product strategies and market initiatives align with where the market is going.

whitePaper | August 26, 2022

The SolarWinds compromise became public in December 2020 and was a massive wake up to the industry. Likely a state-sponsored attack, it compromised potentially thousands of governments and other high-profile organisations across the globe. Many organisations are currently in damage control following the breach. Many of them are unsure if the perpetrators have entered, spread and are still persistent within their environment - even after they shut down the SolarWinds Platforms.

whitePaper | August 24, 2022

In the last couple of years, “zero trust” has gained significant traction in the cybersecurity realm as a means to protect networks and increase security across organizations. In part, the growing popularity of this security model can be attributed to the shift to hybrid working practices that call for a more secure work environment whether on- or off-premises.

whitePaper | October 31, 2022

As cloud-based software solutions become prominent, discussions continue to revolve around security. When organizations implement a cloud-based solution, they put their trust in the solution provider to protect their data and deliver a secure platform.

whitePaper | August 31, 2022

The benefit awareness cybersecurity awareness training, particular phishing simulations, have gained wide acceptance in business and the public sector.

whitePaper | January 23, 2020

With the accumulation of big data, dramatic improvements in computing power, and continuous innovation in Machine Learning (ML) methods, Artificial Intelligence (AI) technologies such as image recognition, voice recognition, and natural language processing have become ubiquitous. Meanwhile, AI poses a significant impact on computer security: on the one hand, AI can be used to build defensive systems such as malware and network attack detection; on the other hand, AI might be exploited to launch more effective attacks.