An anomaly is referred to a behavior, a result, an action or a sequence of actions that are different from the normal or expected behavior, result or pattern. One can think of it as an irregularity or a divergence from general practice.
The identification and detection of the above-mentioned behaviors or actions are simply defined as anomaly detection. Hence, pinpointing the activities or data points that do not satisfy the expected or natural pattern is called anomaly detection. A key asset to detect an anomaly in an IT environment is the Zero Trust security framework, which will be discussed later in the article.
In cybersecurity, anomaly detection helps in finding structural defects, security misconfigurations and potential digital attacks. There are three main sub-sections that operate under the banner of cybersecurity anomaly detection;
There are three common types of anomalies that indicate a cybersecurity threat:
Any activity that takes place at an unexpected or odd time is considered a time anomaly. It is a best practice to put in place a specific timing for all activities in your organization for all users.
In this case, it will be identified whenever an activity takes place at a time it is not scheduled to do so. Here is a real-life example of a time anomaly: An employee account that is scheduled to be active from 9 am to 5 pm, but his account is logged in at 10 pm.
When multiple activities are performed simultaneously or in a short period of time by a host or an employee, count anomalies are observed. The administrators should specify the number of activities that can be performed in a given time period.
If that number (baseline) of specified activities is exceeded, the system is alerted that a count anomaly is observed. For example, if you have set the maximum number of configuration changes for a router to 11, but the router undergoes 20+ configuration changes.
When an unforeseen sequence of events takes place, a pattern anomaly is observed. If these events take place individually, they may not be considered an anomalous activity, but together they deviate from the expected pattern; hence the name “Pattern Anomaly.”
A baseline for the expected pattern of activities should be created within the organization that all users and hosts must follow. Then all activities that take place can be compared with the baseline pattern to point out if there is an anomalous behavior in the pattern.
In the current hybrid work routine, we see that access to corporate data and apps needs to be provided to mobile users, third-party contractors, and desktop users simultaneously. However, the risks of a potential digital attack have also risen. The Zero Trust model allows the least privileges required for a task to be completed and generates a warning if an anomalous activity is performed.
Basically, the Zero Trust model is a cybersecurity framework that treats all users of the cyber environment equally. It demands that all users are authorized, continuously validated and verified before being granted access to the resources and data of the organization.
The Zero Trust framework operates under the following principles:
The Zero Trust model allows organizations to automate their identity verification and monitoring systems. This provides them with high flexibility in security levels. This framework allows the organizational security teams to prepare a cushioning response to consumer activity. Meaning that immediate action can be initiated once an anomaly is detected.
Customers and employees only get the least required access to complete an action. This allows the security teams to diminish a threat timely and minimize the exposure of confidential applications and data. The Zero Trust model ensures that every entry request is automatically inspected thoroughly before being awarded approval.
Security teams continuously monitor the process of accessing the corporate data and resources that users and employees follow. If a deviation from the normal pattern is observed, warnings are issued, and threat mitigation starts. Continuous monitoring helps point out and terminate inbound and external cyber threats.
The aim of the Zero Trust model is to prevent advanced cyber threats from causing harm to the organization. Zero Trust framework ensures compliance with HIPAA, CCPA, FISMA, GDPR and other data privacy laws.
A business is based on four key components: data, assets, applications and end-users/customers.
Zero Trust strategies can manage corporate data’s anomaly detection, access, and permission levels. Additionally, any unauthorized downloads or information transfers within your business environment can be identified easily.
Along with cloud-based workloads, digital attackers also target business assets like virtual machines, containers and functions. Zero Trust framework offers the appropriate tools to tackle such situations. Businesses focus their security efforts by pinpointing the critical assets and using role-based access to verify an access request.
The usage and accessibility of applications are continuously monitored at runtime. This allows the security teams to understand user behavior and detect deviations from the set-out pattern. Zero Trust treats any change in the usage as anomalous activity.
The customers or end-users of a business include partners, employees, and 3rd-party contractors as well. They all use different access rights and identities and access corporate applications and data from managed and unmanaged devices. This gives rise to many management and security challenges that can be tackled with the Zero Trust security model.
In the cyber world, anomalies indicate a potential attack, so detecting an anomaly has become crucial to cybersecurity. Increasing digital security threats demand an updated and fool-proof security infrastructure. Therefore, Zero Trust security is an excellent way to detect and mitigate an anomaly in your IT infrastructure.