FireEye Central Management Centralize device and intelligence management to correlate data across attack vectors

whitePaper | October 21, 2022

The purpose of this document is to help technically-oriented professionals understand the security-related value BeyondTrust can bring to your organization. BeyondTrust can help your support organization stay secure and compliant, while improving the efficiency and success of your organization with a better end-user support experience.

whitePaper | January 24, 2023

Cloud-based software delivery has increasingly become the norm in today’s world, owing to the elasticity, scalability, and economy of cloud architectures. Arista has established a leadership position in the delivery of reliable and secure cloud networking and services management through the introduction of CloudVision®, a single unified AI/ML-enabled network management platform supporting every place in the cloud – and CloudVision is now available in an “as-aService” delivery model in the cloud.

whitePaper | April 13, 2023

Those high profile data breaches led to a swift response from the Government with the penalties for serious or repeated privacy breaches increased from $2.22 million to a minimum of $50 million at the end of December. Since then, the Government has released the Privacy Act Review Report and the 2023-2030 Australian Cyber Security Strategy that signpost a significant shift for Australia’s cyber landscape. Critical infrastructure; personal information; cyber security; dealing with ransomware attacks – all are likely to be shaken up.

whitePaper | January 18, 2023

Row Level Security (RLS) in Tableau refers to restricting the rows of data a certain user can see in a given workbook or data source at the time they view the data. It contrasts with permissions within Tableau Server (or Tableau Online), which are used to control access to content and feature functionality.

whitePaper | December 4, 2019

This paper describes a distributed anomaly detection approach designed to accurately track actions performed by adversaries across a network. The illustrated approach involves running multiple machine learning models on both endpoints and the network as well as on a centralized backend, and includes communication and replication of learned states between these models.

whitePaper | November 29, 2022

We live in an intensely data-driven world, where data loss is unacceptable and quick access to information with real-time analytics driven by machine learning and artificial intelligence is at the core of decision making. Effective data protection is a critical component of every successful business. Now, more than ever, organizations are looking at their data protection strategies through a new lens. They are evaluating old practices, with a focus on making data protection a hands-off, efficient solution they can rely on without applying extensive IT resources. This can be accomplished through standardizing on a vendor with a comprehensive data protection offering, single management capabilities, and support across a diverse network of systems on-premises, in public and private data centers, in multiple clouds, and in remote office/branch offices (ROBO) and edge environments.