Cognitive Bias: The Root Cause of Cybersecurity Errors

Cyber security is one of the biggest challenges faced by organisations around the world. Although cyber security technology and tools have developed rapidly, threats posed by human factors remain a significant problem. Cognitive biases—distortions in human thinking and decision-making—are often the root cause of many cybersecurity errors. This article will explain how cognitive biases influence behaviour in the context of cybersecurity and why this is a serious problem in maintaining data security.

What is Cognitive Bias?

Cognitive bias is the tendency of the human brain to make irrational decisions based on certain perceptions or experiences. It is a pattern of thinking that is often unconscious, which can lead individuals to make incorrect or suboptimal decisions. This bias is usually based on incomplete information, stereotypes, or a tendency to follow established norms.

In the context of cybersecurity, cognitive bias can cause employees or individuals to make mistakes in identifying or responding to threats, ignore potential risks, or feel overly confident in existing security systems.

Read: Psychology's Role in Raising Cybersecurity Awareness

Types of Cognitive Biases that Affect Cybersecurity

Confirmation Bias

Confirmation bias is the tendency for people to seek out information that supports their existing beliefs or views. In the context of cybersecurity, a person may ignore signs of a cyberattack if they do not match their initial perception of the system's security. For example, an employee who believes that the company's security system is very strong may ignore phishing emails because they believe that such threats will not get past the company's cyber defences.

Overconfidence Bias

This bias occurs when a person feels overly confident about their abilities or knowledge in a particular field. In cybersecurity, employees or IT teams may feel confident that they have taken all necessary steps to protect data, and therefore tend to ignore threats that seem minor. This overconfidence can lead to negligence, such as not updating software or not performing regular security audits.

Recency Bias

This bias refers to the human tendency to focus more on the latest information or current events and ignore past events that may be more relevant. In cybersecurity, employees may be more alert to recent threats, such as the massive ransomware attacks recently reported in the news, while lesser-known but equally dangerous threats may be overlooked.

Status Quo Bias

Status quo bias makes individuals more likely to choose to maintain the existing situation or habits rather than take actions that change the status quo. In cybersecurity, this could mean that someone is reluctant to follow new security practices or update security policies because they feel comfortable with existing procedures. This can lead to vulnerabilities as cyberattack technologies and methods evolve rapidly.

Attribution Bias

This bias refers to the tendency to blame external factors or other people for mistakes that occur, while personal or internal failures are often overlooked. In the context of cybersecurity, teams may blame end users for data leaks or phishing attacks, when in fact the problem may lie in a lack of training or inadequate security policies.

The Impact of Cognitive Biases on Cybersecurity

Errors caused by cognitive biases often have a significant impact on cybersecurity. Some of the main impacts include:

• Failure to detect threats: Confirmation bias and overconfidence bias can cause a person to ignore signs of an attack, even when the threat is obvious. This can result in attacks going undetected until it is too late to deal with them.
• Poor decision-making: Cognitive biases can lead to poor decisions regarding preventive measures or responses to cyber threats. For example, status quo bias can hinder the implementation of new, more effective security technologies.
• Reduced training effectiveness: If security training is not designed to address cognitive biases, its effectiveness may be reduced. Employees may continue to behave unsafely even after receiving training, as biases such as overconfidence or recency bias make them feel immune to threats.

Overcoming Cognitive Bias in Cybersecurity

To reduce the impact of cognitive bias, organizations can take the following steps:

1. Awareness-Based Training: Cybersecurity training that includes awareness of cognitive bias can help employees recognize their tendency to make poor decisions. Through simulations and real-life examples, employees can be trained to be more aware of their own biases.
2. Automation and Real-Time Monitoring: Reducing reliance on manual decisions by adopting automated cybersecurity solutions, such as real-time threat monitoring, can help mitigate the impact of cognitive bias. Automated systems can detect threats based on objective data without being influenced by human bias.
3. Structured Decision-Making Processes: Implementing standard procedures for cybersecurity decision-making can help reduce the effects of cognitive bias. For example, requiring double-checking for every major security decision or using data-driven risk assessments can improve the quality of decision-making.
4. Regular Evaluation and Review: Conducting regular security audits and evaluating the effectiveness of policies and tools used can help identify whether cognitive biases are influencing important decisions.

Read: Improving Cybersecurity Behavior Among SME Employees

Conclusion

Cognitive bias is one of the main root causes behind human error in cybersecurity. By understanding how this bias works and its impact on decision-making, organizations can take more effective measures to protect their systems and data from cyber threats. Addressing cognitive bias through training, automated technology, and structured decision-making can help reduce the risks caused by human error.