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How machine identities are the key to successful identity management

 1 year ago
source link: https://venturebeat.com/security/how-machine-identities-are-the-key-to-successful-identity-management/
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How machine identities are the key to successful identity management

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Securing digital identities is a problem for many organizations. In fact, according to the Identity Defined Security Alliance (IDSA), 84% of organizations have experienced an identity-related breach. 

Part of the challenge of identity management is the identities that organizations need to manage aren’t just human, but machine-based. 

Today, enterprise identity security provider SailPoint Technologies Holdings, Inc., released a new research report surveying 300 global cybersecurity executives and revealing that machine identities make up 43% of all identities within the average enterprise, followed by customers (31%) and employees (16%). 

This highlights that organizations need to have a solution for managing digital machine identities in real time if they want to secure their environments against the latest threats. 

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The identity threat landscape 

Over the past few years, the identity sprawl created by the adoption of new technologies and cloud-based apps have increased complexity for security teams dramatically. Today, machine identities now outweigh human identities by a factor of 45 times on average, with the average employee having over 30 digital identities

SailPoint’s research also anticipates that this sprawl will continue, estimating that the total number of identities will grow by 14% over the next 3-5 years. 

Yet, many organizations still have a long way to go before they’re ready to confront the identity threat landscape. 

“Our report shows that 45% of companies are still at the beginning of their identity journey. This means they have the unique opportunity to take advantage of today’s technology to build a comprehensive, [artificial intelligence] AI-enabled approach to identity security from the ground up,” said Matt Mills, SailPoint president of worldwide field operations. 

“As enterprise identity needs move beyond human capacity, this approach has quickly become table stakes. Not only that, but identity security has risen to the top as business-essential to securing today’s enterprise,” Mills said. 

In practice, an artificial intelligence (AI) and machine learning (ML) centric approach is essential for detecting digital identities in real time. This appears to be recognized by organizations, with 50% of respondents indicating they’ve implemented AI/ML models to boost their capabilities. 

SailPoint’s own identity security cloud platform leverages AI and ML to automatically identify user and machine identities throughout enterprise environments, so that security teams can more effectively manage and secure them. This approach serves to increase visibility over user access risks. 

The identity management market 

SailPoint falls within the global identity and access management market, which researchers estimate will grow from a value of $13.4 billion in 2021 to $34.5 billion in 2028. 

The vendor remains a significant player in the market, in August reporting that it has raised annual recurring revenue (ARR) of $429.5 million.  

It’s competing against a number of other key players in the market including Okta, an identity platform provider which offers a unified IAM solution with lifecycle management to automatically onboard and offboard employees and contractors, and a single sign-on solution that IT teams can use to monitor and manage user access. 

Okta recently announced raising $383 million in total revenue for during the fourth fiscal quarter of 2022. 

Another competitor is CyberArk, a vendor that provides an enterprise privileged access management solution for automatically discovering and onboarding credentials and secrets used by human and machine identities. It also offers automated password rotation and the ability to authenticate user access through a single web portal.

Earlier this year, CyberArk announced raising ARR of $427 million. 

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