IT teams must implement a Zero Trust security strategy as apps, data, and identities move outside the traditional corporate perimeter.
In a Zero Trust environment, all access is verified, whether the connection is from a network inside or outside your organization. This eliminates lateral movement and unauthorized access to sensitive resources.
Identity Management
Identity Management helps organizations secure identity data and user access to enterprise resources. This is done using various digital identity technologies, such as passwords, multi-factor authentication (MFA), single sign-on (SSO), and biometrics.
Traditionally, identity management solutions have primarily been used to manage the identities of people and devices that require access to network resources. This includes internal employees, external visitors, contractors, vendors, and other business partners.
The most effective identity management solutions will allow you to establish and maintain one digital identity for each user or device, regardless of location or access. These identities are tracked, managed, and changed throughout their access lifecycle.
Zero Trust Network Access or ZTNA is a security model that requires all users, whether in the enterprise or externally, to be authenticated, authorized, and continuously validated for security configuration and posture before being granted or keeping access to applications and data.
To accomplish this, Zero Trust relies on a set of technologies, including asset management, application authentication, access control, and network segmentation. It also includes a combination of automation and analytics.
For example, if a user’s device or app is deemed untrustworthy, the platform may block that access or notify them to update outdated software. This can help prevent unauthorized changes from happening in the first place.
Access Control
Access control involves identifying who attempts to access secured company information, areas, or assets and verifying that they have the correct permissions. This can be done using passwords, PINs, biometric readings, or a combination of these options.
Zero trust is a security model that requires users to prove their authenticity whenever they access network applications or data. This is often called the principle of least privilege, and it’s based on the fact that no one should be automatically granted access to anything without much effort and verification.
It’s also based on micro-segmentation, breaking security perimeters into small zones to maintain separate access for different network parts. This allows organizations to limit the potential impact of a lateral movement attack, where a hacker moves across a network after gaining access.
Implementing a Zero Trust security framework is the most effective approach combining risk-based multi-factor authentication, identity protection, next-generation endpoint security, and robust cloud workload technology with automated context collection and response. This approach ensures that user and system identities are verified, access is granted considering the current and historical activity, and that the health of endpoints is checked regularly.
Zero Trust is a framework that can help companies meet their digital transformation goals while reducing risk and complexity and maintaining resilience. However, this approach needs to be supported by the right resources.
Automation
Automation is an emerging technology that automates workflows and processes to save time and reduce costs. It enables businesses to deliver on digital transformation goals, improve customer experience and keep data security at the top of their priorities.
A Zero Trust approach to network access requires a robust framework for managing assets and identity, including user accounts and digital artifacts like software updates and security configurations. This framework should enable IT and security teams to work together in a single open language while ensuring access decisions’ accuracy.
The framework should also include risk-based conditional access to prevent interrupting workflows when risk levels change. This ensures continual verification and minimizes user impact if an outsider breach occurs.
To achieve this, security teams must continuously verify devices and apps by assessing attributes such as location, origin, time, etc. Additionally, they should consider behavioral data such as recent activity and multi-factor authentication.
As organizations expand their networks, increase data volumes, and introduce new devices, keeping up with access requests becomes more challenging. This challenge increases the importance of Zero Trust Network Access, which shrinks attack surfaces by default.
Analytics
Analytics is a diverse field of computer science that uses data and math to answer business questions, discover relationships, predict unknown outcomes, and automate decisions. It combines data modeling techniques with artificial intelligence and machine learning, allowing it to uncover new knowledge and solve complex problems.
The analytics market is booming, with hundreds of firms offering technology and services to help organizations store, access, analyze, and present data. These include data management and visualization tools, advanced analytics, and prebuilt analytics solutions.
Despite the booming market, there are some challenges to consider when implementing an analytics strategy. First, business leaders must be able to quickly and easily access insights to inform their decision-making. Next, they must understand what those insights mean and how they impact business performance.
To achieve this, businesses must implement tools that put easy-to-understand insights into the hands of more people. This can be done by embedding insight into front-line applications or automatically triggering relevant decisions.
This type of technology requires a centrally managed data platform and robust and secure data collection, storage, and access. It must also provide version control and transparency about data and model use. This is necessary to ensure the accuracy of analytics and support effective deployment and monitoring of the models.
