The Impact of Cognitive Bias on Cyber–Intelligence. How to Avoid Mistakes in Cybersecurity Analysis
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The impact of Cognitive Bias on Cyber-Intelligence: How to avoid mistakes in Cybersecurity Analysis.
In a rapidly evolving world, the quality of intelligence plays a significant role in everything the world is leaning towards. However, even the most skilled analysts can fall victim to cognitive biases when processing information, which could result in distortion of a perceived threat. These biases often affect cloud judgment, leading to false conclusions and flawed decision-making. In cyber-intelligence where accuracy is crucial, understanding how information is transformed into actionable intelligence is important for effective threat analysis and risk management.
What is Cyber-Intelligence?
Cyber-intelligence is gathering, processing, analysing and disseminating information that identifies, tracks, and predicts threats, risks and opportunities inside a cyber domain, helping decision-makers address the ever-growing landscape of cybersecurity threats.
The Flow of Information to Intelligence
Intelligence is derived from data, which after thorough analysis and processing, transforms into valuable information and eventually actionable intelligence. This highlights how raw data is transformed into intelligence that helps in better decisions.
Cognitive Bias in Cyber-Intelligence
In 2014, a prominent global corporation suffered a major cyberattack, leading to the exposure of sensitive data. At the time of the attack, the company’s cybersecurity team believed a rival nation-state actor carried out the attack. This assumption stemmed from a cognitive bias — the anchoring bias, where conclusions are carried from the piece of information, hence, leaving room for little adjustment. This was because an IP related to a known hacker was discovered earlier in the investigation.
However, as time went by, they discovered that they had gone about the investigation wrongly because they had held on to a pre-existing judgement, clouding the outcome of the investigation. These threat actors had been smart enough to disguise themselves as a nation-state actor.
Additionally, during the course of the investigation, senior executives discussed the attack, believing that a state actor carried out the attack at the time. This belief went unchallenged by junior analysts who, though might have held different opinions at the time. This situation exemplified the bandwagon effect, where individuals follow a popular opinion without questioning the alternatives.
Humans have analytical understanding, consisting of art and science. The art side includes personal beliefs, experiences and biases, while the science is rooted in the analytical framework. Unfortunately, humans are prone to biases that can affect performance.
Cognitive Bias.
Cognitive bias is an error in thinking when we try to process information. These biases occur because we rely on mental shortcuts to simplify things. Another common cognitive bias is the framing effect, which refers to how the presentation of Information can alter the information, thereby influencing decision-making. A classic example from Robert Clark’s book: Intelligence Analysis. A Target Centric Approach illustrates this:
In 1982, a group of doctors were presented with two treatments for a condition. Treatment A was framed with a 93% survival rate, while Treatment B had a 10% mortality rate. Now, mathematically, these outcomes were the same, but it was observed that the Doctors chose Treatment A because of the positive framing. This shows how information is communicated can significantly affect results even when the data remains unchanged.
Why Recognizing Cognitive Bias Matters?
Information collected could be distorted, leading to wrong or poor analysis, and decision-making leading to serious damages. Incorrect decisions resulting from bad analysis can have severe consequences. Understanding cognitive bias could help mitigate these risks:
1. Ensuring objectivity: Maintaining neutrality while gathering information could eliminate confirmation bias. Confirmation bias tends to favour information that supports one’s pre-existing belief. One common Confirmation bias today is listening only to a particular news outlet that aligns with your political objective.
2. Improving Accuracy: Recognizing bias helps to eliminate errors while gathering information, for instance, relying too much on a piece of initial information (anchoring). Understanding this bias could help enhance precision in information gathering.
3. Comprehensive Analysis: Understanding bias could encourage analysts to consider different perspectives when gathering and processing information.
4. Better Decision-making: Since decision-makers rely on accurate intelligence to make better decisions, it is very important that the intelligence given to them is correct to avoid severe consequences, which could be a big as national security issue.
Cognitive biases, such as anchoring, bandwagon, and framing effects, significantly shape how we perceive, process and interpret information in cyber-intelligence. Recognising these biases is essential for improving the accuracy of intelligence. By understanding the potential for distortion, analysts can make improved decisions, which enhances objectivity and improves the overall quality of cyber-intelligence, thereby reducing the risk of errors in judgment. In a world where decision-making in cybersecurity is crucial, unbiased intelligence is vital in making informed decisions.
