Carahsoft, in conjunction with its vendor partners, sponsors hundreds of events each year, ranging from webcasts and tradeshows to executive roundtables and technology forums.

Government Events and Resources

Events

Plurilock Partners With Carahsoft to Bring Continuous Identity Assurance to Federal Agencies
Plurilock Security Solutions

Security Threats to Consider When Using Amazon Workspaces


Event Date: August 09, 2022

The world spends a lot of time locking down logins. Yet resources are scarce when it comes to rapidly detecting and monitoring compromised credentials and sessions.

Plurilock DEFEND offers identity assurance and compromise detection, alerting IT security personnel to potential threats in real-time. The platform runs invisibly, providing continuous identity detection and endpoint visibility in the background as users work. This capability enables DEFEND to augment existing multi-factor authentication (MFA) and single sign-on (SSO) solutions while enhancing security awareness and reducing friction.

This webinar outlined how Plurilock's enhanced functionality supports Amazon WorkSpaces by providing continuous identity assurance using behavioral biometrics. DEFEND eliminates the opportunity for an attacker to access sensitive information in the network or detonate a malicious payload.

This webinar covered the top security threats to consider when using Amazon WorkSpaces. Attendees learned: 
  • How security threats in Amazon WorkSpaces environments can impact your organization
  • How Plurilock DEFEND identity assurance technology can protect Amazon Workspaces environments 
  • Plurilock’s recent success with a California-based pension fund, using DEFEND’s new VDI functionality 

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Resources

A Compact Guide to Large Language Models
Resources

A Compact Guide to Large Language Models

Large language models are becoming increasingly important in a variety of applications such as natural language processing, machine translation, code and text generation and more. Download this guide to gain insights into large language models (LLMs).


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