The biggest challenge that present-era industries are dealing with is keeping mission-critical information safe and out of reach of cyberpunks. However, the task doesn’t seem as easy as it sounds. Exploding data expands the attack surface and multiple entry points are making things difficult to cater to. This is why businesses of all sorts and types need hand-holding when it comes to identifying the information data risk.
This is where FAIR comes into the picture. Known as one of the most viable risk evaluation methodologies, FAIR is viable to control the risks, provided you use it correctly. For every FAIR beginner, this guide will be of great help as it explains some of the most crucial aspects.
This is a non-profit organization formed with the single goal of providing the world with a crisp and strategic information risk analysis approach so that risks are identified in the infancy stage, damages are controlled, and the least data is at risk if an attack still happens.
Cybersecurity and information security professionals across the world look to this institute to learn the soundest practices that they can implement at work to manage, measure, and identify lethal information risks. The institute is responsible to frame, upgrade, and innovate the FAIR cyber risk framework.
Professionals can join the membership of the institute to stay updated about key inputs from the information risk analysis industry.
You have two membership options to choose from. The first membership is free, General Membership, and offers limited benefits like blog summary, local chapter training, and so on.
If you’re seeking access to the best possible information risk resources and assistance then you should go for Contributing membership, which is a paid option. With this membership, you will get full access to the resource library, webinars, workshops, and every other initiative that FAIR Institute will be taking toward the betterment of information risk management and analysis.
To have better clarity on Fair risk methodology let us explain that FAIR or Factor Analysis of Information Risk is a globally recognized risk framework that organizations of all sorts can refer to while identifying cyber information risks. Because of its great viability and positive outcomes, it has emerged as a VaR or Value At Risk framework for businesses dealing with operational and cybersecurity risk assessment.
Have a look at a few key traits and information about this information risk framework.
All in all, the framework is equipped with every feature and facility that is required for immediate and accurate information risk detection. It offers great motivation for quick risk mitigation.
As FAIR comes into action, it sets its sight on the complication of multiple factors that can establish the risks in a given ecosystem. FAIR explains that a deeper analysis of all these factors is important because it provides a broader picture of every risk and helps one to understand how these new risks are linked with existing risks.
FAIR factor analysis provides users with a crisp and updated list of ways to identify the features that can lay the foundation of a specific risk. To make it happen, the model is using the scenario-modeling construct. With its help, it’s easy to simulate the predicted risks and scenarios.
When compared to another framework, FAIR has a different method of operation that is more accurate and scientific. It aligns with COSO, ITIL, ISO/IEC 27002:2005, COBOT, etc. FAIR acts like an engine that does analytics and computation.
FAIR is based on a highly strategic approach that involves:
The deeper level of understanding is only possible when you’re aware of the FAIR’s founding components. Mainly, this methodology is based on four components that include:
They can be any object, action, person, or element, capable of harming a resource or asset. A typical threat takes the help of the application’s loopholes to initiate the loss events against any asset or resource by force or trick.
There is no specific definition of a threat because everything from a typhoon to a corrupted syntax is a threat. A threat is anything capable of causing direct or indirect harm to an asset.
With the help of the FAIR model, it’s easy to have a threat profile. The threat profiling process is extensive and involves keeping the focus on primary intent, risk tolerance, collateral damage, motives, and many other factors.
Assets could be tangible or intangible. All the data-driven devices that an organization is using to process data are tangible assets. It involves computers, laptops, servers, and so on. The Data file is an example of an intangible asset. Both should be part of the security analysis as they both can be under attack and cause huge damage.
The third component of FAIR assessment is an organization which refers to the entity under observation. It could be a start-up, enterprise, or small-scale business. Basically, an organization is one where a group of people work and exchange a huge deal of data.
If organizations are not concerned about protecting that information, its profitability, brand value, and credibility could be compromised severely. Depending upon the seriousness of the risk, an organization can cease the operational functionality completely.
As organizational information is always at risk, FAIR risk methodology can help to protect it. With its help, organizations gain insights to identify direct and indirect information risks correctly.
The last FAIR methodology component is the external environment of an organization. The external factors are those that are beyond the authorization area of an organization. Mostly, it includes regulatory frameworks, legislative roadblocks, and industry competitors.
If you want FAIR assessment to bring dependable results then you need to make sure that FAIR-enabled risk checks are done correctly. To begin with, you should correctly identify the cyber network and its complexity. Doing so will help you understand which cyber assets should be under consideration.
Next, you should sort out the applications or network assets that have 3rd party access to your data or information of any sort.
The foundation of result-driven FAIR risk assessment is having sound knowledge of what it can handle.
Well, you can use this framework to analyze the strategic, compliance, operational, reputational, and transactional risks.
Once you know which risks you’re going to take under consideration, start with the FAIR model risk assessment and use it to form a viable risk methodology.
Once you recognize the potential risks that can make your business vulnerable, you can start the FAIR-driven assessment process to develop strategies to reduce risks and resolve the challenges.
This risk assessment model is extensive and features ten steps that are later categorized into four stages that we have explained next.
This is the first stage of the evaluation process and it comprises two actions. The first action is to know which all assets could be under attack and have a risk possibility. The second action of this stage is to know the threat resources.
The foundation of this stage is the probability-based model that helps in figuring out the probability of a risk and its related damage. This stage should collect feedback from top management, CISO, and other cybersecurity professionals.
In the second stage, all the action happening revolves around collecting data related to metrics like Loss Event Frequency, Threat Event Frequency, Control Strength, and Threat Capability. Each of these metrics provides a deeper insight into cybersecurity risks. For instance, Threat Event Frequencies are the estimated frequencies of threat agent actions that are capable of causing any damage in a given time.
It revolves around PLM. PLM solving queries like an anticipated loss to an organization from primary and secondary loss events, what are worst-case scenarios, and so on.
This stage takes care of both the primary and secondary losses concerning the stakeholders. Let’s understand what these two loss types mean.
Primary loss is incurred because of any direct loss event. It could involve lost revenue or any outdated asset of an organization.
By secondary loss, we meant the loss incurred because of events that are not directly linked with primary stakeholders but still have a certain impact on the organization and its key operations. Secondary risks have definite potential to inflict and reduce the performance of an organization.
The last stage of the FAIR’s procedure involves articulating the risks to everyone who wants to use this assessment for decision-making. The methods involved in the process are:
If you manage to successfully pass all the stages of FAIR risk analysis, you will have enough risk assessment data and you should know how to use or deal with it. Most of the data will help you figure out parameters such as loss magnitude, LEF, and FAIR loss magnitude. The FAIR loss magnitude entails both the secondary and primary loss data.
In secondary loss data, you will have details related to customer loss, penalties, and brand damage costs. Primary loss data is all about details related to asset losses, recovery costs, and many other losses.
As the assessment makes use of the confidence scoring method and obtains a wide range of data. With diligent use of that data, it’s possible to improve the security posture, identify the gaps in the existing security framework instantly, and take immediate action. This data holds great importance for the CISO as it can improve the security framework of an organization and work on key metrics.
As attention will be on what’s important, the cybersecurity team will have more time to take immediate action.
The efforts you will put in adopting or referring to the FAIR’s methodology for managing the risk will never go wasted because:
Despite offering so many benefits and advantages, FAIR is not flawless. There are certain drawbacks that are certain with this framework. For instance:
For organizations dealing with information risk, FAIR is a great framework to adopt because it can nudge the current risk management efforts in the right direction and encourage you to give more focus to the analytics. Even though the model does a great job, it’s not flawless. It’s wise to consider the model as a suggestive methodology and apply your intelligence and analysis to finalize the information risks.
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