McAfee MVISION Cloud
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McAfee MVISION Cloud
Additional Info
| Company | McAfee |
| Website | https://www.mcafee.com/enterprise/en-us/solutions/cloud-security.html |
| Company size (employees) | 5,000 to 9,999 |
| Type of solution | Software |
Overview
McAfee MVISION Cloud, part of the McAfee MVISION portfolio, is the first cloud access security broker (CASB) solution available to bring together data and threat protection across SaaS, IaaS, and PaaS. With MVISION cloud, organizations can securely take advantage of the cloud to accelerate their business.
Organizations use McAfee MVISION Cloud to mitigate cloud risk by fulfilling their shared security responsibility in the cloud. Key use cases include:
Enforcing data loss prevention (DLP) policies across data in the cloud.
Preventing unauthorized sharing of sensitive data to the wrong people.
Blocking sync/download of corporate data to personal devices.
Detecting compromised accounts, insider threats, and malware.
Encrypting cloud data with keys that only you can access.
Auditing the configuration of IaaS environments like AWS and Microsoft Azure.
Integration with McAfee Device Data Loss Prevention (DLP) provides universal data protection from device to cloud. This results in a seamless, unified data protection experience – minimizing data loss risks risk while maximizing business agility.
How we are different
Visibility into data, context and user behavior: Provides visibility and control across all cloud services, employing a combination of API- and proxy-enabled approaches, with DLP policy that can be extended from devices to the cloud. This includes content scanning, logging and activity monitoring and threat and malware detection.
Centralized management: Delivers consistent and comprehensive management across public cloud services spanning the SaaS, PaaS, and IaaS spectrum, like Microsoft Office 365, Salesforce and Amazon Web Services (AWS).
Advanced Threat Protection: Protects against malware and external and insider threats through UEBA (User and Entity Behavior Analytics) driven by machine learning built for the scale and elasticity of cloud environments.
